Goddard Institute For Space Studies Research Articles

Coupled Stratospheric Ozone and Atlantic Meridional Overturning Circulation Feedbacks on the Northern Hemisphere Midlatitude Jet Response to 4xCO2

Abstract Stratospheric ozone, and its response to anthropogenic forcings, provides an important pathway for the coupling between atmospheric composition and climate. In addition to stratospheric ozone’s radiative impacts, recent studies have shown that changes in the ozone layer due to 4xCO2 have a considerable impact on the Northern Hemisphere (NH) tropospheric circulation, inducing an equatorward shift of the North Atlantic jet during boreal winter. Using simulations produced with the NASA Goddard Institute for Space Studies (GISS) high-top climate model (E2.2), we show that this equatorward shift of the Atlantic jet can induce a more rapid weakening of the Atlantic meridional overturning circulation (AMOC). The weaker AMOC, in turn, results in an eastward acceleration and poleward shift of the Atlantic and Pacific jets, respectively, on longer time scales. As such, coupled feedbacks from both stratospheric ozone and the AMOC result in a two-time-scale response of the NH midlatitude jet to abrupt 4xCO2 forcing: a “fast” response (5–20 years) during which it shifts equatorward and a “total” response (∼100–150 years) during which the jet accelerates and shifts poleward. The latter is driven by a weakening of the AMOC that develops in response to weaker surface zonal winds that result in reduced heat fluxes out of the subpolar gyre and reduced North Atlantic Deep Water formation. Our results suggest that stratospheric ozone changes in the lower stratosphere can have a surprisingly powerful effect on the AMOC, independent of other aspects of climate change.

Assessing acetone for the GISS ModelE2.1 Earth system model

Abstract. Acetone is an abundant volatile organic compound (VOC) in the atmosphere, with important influences on ozone and oxidation capacity. Direct sources include chemical production from other VOCs and anthropogenic emissions, terrestrial vegetation, biomass-burning emissions, and ocean production. Sinks include chemical loss, deposition onto the land surface, and ocean uptake. Acetone also has a lifetime that is long enough to allow transport and reactions with other compounds remote from its sources. The NASA Goddard Institute for Space Studies (GISS) Earth system model ModelE2.1 simulates a variety of Earth system interactions. Previously, acetone had a very simplistic representation in the ModelE chemical scheme. This study assesses a more sophisticated acetone scheme in which acetone is a full 3-dimensional tracer with explicit sources, sinks, and atmospheric transport. We first evaluate the new global acetone budget in the context of past literature. Estimated source and sink fluxes fall within the range of previous models, although total atmospheric burden and lifetime are at the lower end of the published literature. Acetone's new representation in ModelE2.1 also results in more realistic spatial and vertical distributions, which we compare against previous models and field observations. The seasonality of acetone-related processes was also studied in conjunction with field measurements, and these comparisons show promising agreement but also shortcomings at high-emission urban locations, where the model's resolution is too coarse to capture the true behavior. Finally, we conduct a variety of sensitivity studies that explore the influence of key parameters on the acetone budget and its global distribution. An impactful finding is that the production of acetone from precursor hydrocarbon oxidation has strong leverage on the overall chemical source, indicating the importance of accurate molar yields. Overall, our implementation is one that corroborates with previous studies and marks a significant improvement in the development of the acetone tracer in GISS ModelE2.1.

Influence of More Mechanistic Representation of Particle Dry Deposition on 1850–2000 Changes in Global Aerosol Burdens and Radiative Forcing

AbstractRobust estimates of historical changes in aerosols are key for accurate constraints on climate sensitivity. Dry deposition is a primary sink of aerosols from the atmosphere. However, most global climate models do not accurately represent observed strong dependencies of dry deposition following turbulent transport on aerosol size. It is unclear whether there is a substantial impact of mischaracterized aerosol deposition velocities on historical aerosol changes. Here we describe improved mechanistic representation of aerosol dry deposition in the NASA Goddard Institute for Space Studies (GISS) global climate model, ModelE, and illustrate the impact on 1850–2000 changes in global aerosol burdens as well as aerosol direct and cloud albedo effects using a set of 1850 and 2000 time slice simulations. We employ two aerosol configurations of ModelE (a “bulk” mass‐based configuration and a configuration that more explicitly represents aerosol size distributions, internal mixing, and microphysics) to explore how model structural differences in aerosol representation alter the response to representation of dry deposition. Both configurations show larger historical increases in the global burdens of non‐dust aerosols with the new dry deposition scheme, by 11% in the simpler mass‐based configuration and 23% in the more complex microphysical configuration. Historical radiative forcing responses, which vary in magnitude from 5% to 12% as well as sign, depend on the aerosol configuration.

Exploring the ENSO modulation of the QBO periods with GISS E2.2 models

Abstract. Observational studies have shown that the El Niño–Southern Oscillation (ENSO) exerts an influence on the Quasi-Biennial Oscillation (QBO). The downward propagation of the QBO tends to speed up and slow down during El Niño and La Niña, respectively. Recent results from general circulation models have indicated that the ENSO modulation of the QBO requires a relatively high horizontal resolution, and that it does not show up in the climate models with parameterized but temporally constant gravity wave sources. Here, we demonstrate that the NASA Goddard Institute for Space Studies (GISS) E2.2 models can capture the observed ENSO modulation of the QBO period with a horizontal resolution of 2∘ latitude by 2.5∘ longitude but with its gravity wave sources being parameterized interactively. This is because El Niño events lead to more vigorous gravity wave sources generating more absolute momentum fluxes over the equatorial belt, as well as less filtering of these waves into the tropical lower stratosphere through a weakening of the Walker circulation. Various components of the ENSO system, such as the sea surface temperatures, the convective activities, and the Walker circulation, are intimately involved in the generation and propagation of parameterized gravity waves, through which ENSO modulates the QBO period in GISS E2.2 models.

The Magic of Environmental Detection and Future Prediction by Satellite

Climate change is one of the important issues that face the world in this technological era. We have used data collected from the publicly available GISTEMP data, the Global Surface Temperature Change data distributed by the National Aeronautics and Space Administration Goddard Institute for Space Studies (NASA-GISS). The data consisted of the mean surface temperature change with respect to baseline climatology corresponding to the period 1951-1980. The data covers the time period of 1961-2019. We studied the change in temperature in the countries like Greenland and India using the regression models. All the regression graphs were plotted in the Spyder software using python. From the regression models we observed the significant rise in temperature in these countries caused due to global warming. These models will help us to predict the change in temperature in future

Research on meteorological temperature prediction based on machine learning

Predicting temperature has been a great challenge in meteorology. Accurate temperature prediction is more conducive to human production and life. This study investigated the ability of artificial neural network (ANN) and random forest (RF) methods to predict short-term monthly temperatures. The study data has been processed from the global surface temperature change estimated by NASA Goddard Institute for Space Studies. The average temperature from three months ago, the average temperature two months ago, and the average temperature one month ago were used as inputs to the application model. Both the models gave comparable results, but the superiority of the artificial neural network model over the random forest model in the present study.

Effect of Carbon Dioxide, Methane and Nitrous Oxide with TCO and Solar Flux on the Earth’s Stratosphere Temperature in Mid-Latitude Region for Period 2000-2018

Abstract The stratosphere is the second layer of the atmosphere and the important of this layer is to contain the ozone layer which absorbs the UV radiation from the Sun. The main objective of this research is to study the effect of GHGs and TCO on the temperature of stratosphere layer in the presence of influence of solar radiation in mid-latitude region, specifically capital Beijing (latitude 40°N; longitude 116°E) in China are taken as a study case, because it is the most city in the world that emits greenhouse gases for the period (2000-2018) selected in this research. The data for GHGs (carbon dioxide, methane and nitrous oxide) are taken from Emissions Database for Global Atmospheric Research (EDGAR), the monthly average data for the total column ozone and temperature are taken from the European Centre for Medium Range Weather Forecasts (ECMWF). While the data for the solar radiation is taken from the NASA Goddard Institute for Space Studies. The data for Sunspot number is taken from Sunspot Index and Long-term Solar Observations (SILSO), all these data are taken for the period (2000-2018) above the capital Beijing. From data analysis and results it found that there is a cooling effect on the stratosphere layer due to increase in greenhouse gases and decrease in the total column ozone, as well as the decreasing in solar radiation leads to this cooling.

Climate change and onchocerciasis: insights from an analysis of public datasets

This study investigates possible correlations between climate change and the prevalence of onchocerciasis. The reported number of individuals treated for the onchocerciasis time series from 2005–2018 was obtained from the World Health Organization Global Health Observatory data repository, whereas the global land-ocean temperature index for the same period was obtained from NASA’s Goddard Institute for Space Studies. The global land-ocean temperature index was used as the independent data, whereas the reported number of individuals treated for onchocerciasis was used as dependent data on the curve fitting regression models. Brazil (p = 0.0037, r2 = 51.86) and Venezuela (p = 0.0012 r2 = 59.85) in South America and Burundi (p = 0.0397, r2 = 30.7), Cameroon (p = 0.0001, r2 = 71.41), Chad (p = 0.0068, r2 = 46.93), Congo (p > 0.05), The Democratic Republic of Congo (p = 0.002, r2 = 56.4), Ethiopia (p < 0.00001, r2 = 77.52), Malawi (p = 0.0097, r2 = 43.96), Nigeria (p = 0.0055, r2 = 48.68), Uganda (p > 0.05), and United Republic of Tanzania (p < 0.00001, r2 = 76.76) in Africa composed the study group. Overall, the patterns observed suggest that climate change may be associated with a rise in the prevalence of onchocerciasis.

Connections between Upper Tropospheric and Lower Stratospheric Circulation Responses to Increased CO2

Abstract There are myriad ways atmospheric circulation responds to increased CO2. In the troposphere, the region of the tropical upwelling narrows, the Hadley cells expand, and the upper-level subtropical zonal winds that comprise the subtropical jet strengthen. In the stratosphere, the tropical upwelling narrows and strengthens, enhancing the Brewer–Dobson circulation. Despite the robustness of these projections, dynamical coupling between the features remains unclear. In this study, we analyze output from the NASA Goddard Institute for Space Studies (GISS) ModelE coupled climate model to examine any connection between the upper tropospheric and lower stratospheric circulation by considering the features’ seasonality, hemispheric asymmetry, scaling, and transient response to a broad range of CO2 forcings. We find that a narrowing and strengthening of upper tropospheric upwelling occurs with a strengthening of the subtropical jet. There is also a narrowing and strengthening of lower stratospheric upwelling that is related to an equatorward shift in critical latitude for wave breaking and the associated strengthening of the subtropical lower stratosphere’s zonal winds. However, the stratospheric responses display different seasonal, hemispheric, and transient patterns than those in the troposphere, indicating independent circulation changes between the two domains.

Analyzing global renewable energy generation trends amid volatile economic and social environments

As renewable energy (RE) rapidly integrates into society to meet the growing demand for affordable and clean energy (SDG 7, United Nations’ Sustainable Development Goal 7), it is crucial to analyze the merits and flaws of renewable energy generation by assessing its impact on the global economy and social wellbeing. This paper performs an investigative study on the correlation and causality between renewable energy, economy, and environmental indicators. The data was gathered from diverse sources, including The Center for Climate and Energy Solutions, National Aeronautics and Space Administration Goddard Institute for Space Studies (NASA GISS), and Our World in Data, for the temperature, carbon dioxide (CO2) emissions, and gross domestic product (GDP) data. Significant Granger p-values were obtained for RE generation’s ability to forecast CO2 emissions and temperature, while discovering a strong positive correlation between CO2 and RE generation. The findings revealed that RE has limited effects on the global economy but has considerable implications on social and ecological well-being.

Investigating hydroclimatic impacts of the 168–158 BCE volcanic quartet and their relevance to the Nile River basin and Egyptian history

Abstract. The Ptolemaic era (305–30 BCE) is an important period of Ancient Egyptian history known for its material and scientific advances, but also intermittent political and social unrest in the form of (sometimes widespread) revolts against the Ptolemaic elites. While the role of environmental pressures has long been overlooked in this period of Egyptian history, ice-core-based volcanic histories have identified the period as experiencing multiple notable eruptions, and a repeated temporal association between explosive volcanism and revolt has recently been noted. Here we analyze the global and regional (Nile River basin) hydroclimatic response to a unique historical sequence of four large and closely timed volcanic eruptions (first a tropical one, followed by three extratropical northern hemispheric events) between 168 and 158 BCE, a particularly troubled period in Ptolemaic history for which we now provide a more detailed hydroclimatic context. The NASA (National Aeronautics and Space Administration) GISS (Goddard Institute for Space Studies) ModelE2.1 Earth system model simulates a strong radiative response with a radiative forcing (top of atmosphere) of −7.5 W m−2 (following the first eruption) and −2.5 W m−2 (after each of the three remaining eruptions) at a global scale. Associated with this, we observe a global surface cooling of the order of 1.5 ∘C following the first (tropical) eruption, with the following three extratropical eruptions extending the cooling period for more than 15 years. Consequently, this series of eruptions is observed to constrain the northward migration of the inter-tropical convergence zone (ITCZ) during the Northern Hemisphere summer monsoon season, and major monsoon zones (African, South Asian, and East Asian) were seen to experience a suppression of rainfall of >1 mm d−1 during the monsoon (JJAS) season averaged for 2 years after each eruption. A substantial suppression of the Indian and North African summer monsoon (over the Nile River headwater region) was seen to strongly affect the modeled river flow in the catchment and discharge at river mouth. River mass flow over the basin was observed to decrease by 29 % and 38 % relative to an unperturbed (non-volcanic) annual mean flow in the first and second year, respectively, after the first (i.e., tropical) eruption. A moderate decrease ranging between 5 % and 18 % was observed after the third and fourth (extratropical) eruptions. These results indicate, in sum, that the first eruption likely produced a strong hydroclimate response, with the following extratropical eruptions prolonging this. These results also support the recently hypothesized association between ice-core-based signals of explosive volcanism and hydroclimatic variability during the Ptolemaic era, including the suppression of the agriculturally critical Nile summer flooding.

Comparisons of simulated radiation, surface wind stress and SST fields over tropical pacific by the GISS CMIP6 versions of global climate models with observations

This study compares the overall performance between versions 2.1 and 3 of National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies (GISS) global climate models (referred to as GISS-E2.1 and GISS-E3, respectively), in simulating the present-day Pacific climate using the CMIP6 protocol. Model physical representations and configurations are extensively changed from GISS-E2.1 to GISS-E3, which result in greatly reduced discrepancies, including ice water path (IWP), ice water content (IWC), radiative fluxes, surface wind stress (TAU), sea surface temperature (SST), precipitation (PR) and column water vapor (PRW), relative to satellite-based observational products over south Pacific oceans. Cloud only IWP (CIWP) shows the largest change, decreasing biases from ∼400 g kg−1 in GISS-E2.1 to 10–20 g kg−1 in GISS-E3. The combination of improved CIWP and the inclusion of snow in GISS-E3 may play roles on reducing overestimated outgoing longwave radiation, overestimated reflected shortwave at the top of atmosphere, and underestimated surface downward shortwave in GISS-E2.1. Both models’ intertropical convergence zones (ITCZs) are, however, located far too north of the equator, as found in radiative fluxes, PR and PRW but not in SST relative to observations. This introduces biases in TAU, PR and PRW over north flank of the equator and north Pacific. Over south Pacific, especially the trade wind regions, the improvements of radiation fluxes, SST, PR and PRW appear to be due to improved TAU associated with inclusion of snow-radiative effects. In particular, GISS-E3 reduces a longstanding too warm SST bias over trade-wind regions, from 4 K in GISS-E2.1 to within 0.5 K, and too cold SST bias over north Pacific Ocean. Although GISS-E3 shows improved geographic patterns of the simulated fields in particular over south Pacific oceans compared to GISS-E2.1, our results suggest that the location of ITCZ needs to be further improved.

The Turning Point of the Aerosol Era

AbstractOver the CMIP6 historical period (1850–2014), aerosols provided the largest negative forcing compared to all other climate forcings via their ability to absorb or scatter solar radiation and alter clouds. Aerosols played an important role in counterbalancing warming by greenhouse gases (GHGs). Here we study aerosol forcing trends in the CMIP6 simulations of the NASA Goddard Institute for Space Studies (GISS) ocean‐atmosphere ModelE version 2.1 (GISS‐E2.1‐G) using a fully coupled atmospheric composition configuration, including interactive gas‐phase chemistry, and either an aerosol microphysical (MATRIX) or a mass‐based aerosol (OMA) module. Simulations of the CMIP6 historical period are analyzed as well as four Shared Socioeconomic Pathway (SSP) future scenarios for 2015–2100: SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5. The main conclusion of this study is that aerosol forcing in the GISS model has reached its turning point, switching from globally increasing to a decreasing trend in the first decade of the 21st century. This result is robust, independent of which aerosol module or SSP scenario is used. Non‐linear aerosol‐cloud interactions dominate as a forcing agent over aerosol‐radiation interactions. Aerosols' ability to counterbalance GHG forcing on the global scale is today at a level comparable to that at the beginning of the last century. In the 1980s, the decade of largest global aerosol loads, aerosols balanced up to 80% of GHG forcing. As a consequence, global warming of the last decades, which is primarily driven by greenhouse gases, has been augmented by the effect of decreasing aerosol cooling in our model. By the end of this century, following the SSP scenarios, aerosols will only counterbalance 0%–20% of GHG forcing, depending on model and on scenario.

Temperature and Precipitation Bias Patterns in a Dynamical Downscaling Procedure over Europe during the Period 1951–2010

The Weather Research and Forecasting (WRF) mesoscale meteorological model is used to dynamically downscale data from the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) CMIP5 version (Model E2-R) over Europe at a 0.25° grid size resolution, for the period of 1951 to 2010. The model configuration is single nested with grid resolutions of 0.75° to 0.25°. Two 30-year datasets are produced for the periods of 1951–1980 and 1981–2010, representing the historic and current periods, respectively. Simulated changes in climate normals are estimated and compared against the change derived from the E-OBS gridded dataset at 0.25° spatial analysis. Results indicate that the model consistently underpredicts the temperature fluctuations observed across all subregions, indicative of a colder model climatology. Winter has the strongest bias of all seasons, with the northeastern part of the domain having the highest. This is largely due to the land–atmosphere interactions. Conversely, spring and summer have the lowest regional biases, owing to a combination of low snow cover (relative to winter) and milder radiation effects (as opposed to summer). Precipitation has a negative bias in most cases, regardless of the subregion analyzed, due to the physical mechanism employed and the topographic features of each region. Both the change in the number of days when the temperature exceeds 25 °C and the change in the number of days when precipitation exceeds 5 mm/day are captured by the model reasonably well, exhibiting similar characteristics with their counterpart means.

Co-inventions, uncertainties and global food security

This paper examines the effects of international collaborative efforts on climate-friendly agricultural technologies on global food security. In particular, we use patent data on environmental technological innovations for OECD countries and global food prices from the period 1990 to 2016. Also, we investigate the impact of uncertainties in weather conditions in terms of rising global temperature created by climate change using data on global surface temperature from the Energy Information Administration and the Goddard Institute for Space Studies (GISS) Surface Temperature Analysis of the National Aeronautics and Space Administration (NASA). We used both impulse response functions and variance error decomposition from a panel Vector Auto-Regressive (VAR) model to examine both the response of global food prices to shocks on the concerned variables and the decomposition of error variance in global food prices. First, our results show that international collaborative efforts on climate-friendly agricultural technologies reduce global food prices while increasing global surface temperature increases food prices. Regarding the variance decomposition of global food prices, results show that surface temperature followed by international collaborations in climate-friendly innovations and other environment-related technologies are the main drivers of forecast error variance in global food prices. The food price variance share associated with greenhouse gas emissions is less when compared to that of technological innovations.

Future Climate Change Under SSP Emission Scenarios With GISS‐E2.1

AbstractThis paper presents the response to anthropogenic forcing in the GISS‐E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non‐interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One‐Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1‐G) and HYCOM (E2.1‐H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1‐2.6, SSP2‐4.5, SSP4‐6.0, and SSP5‐8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high‐mitigation scenarios SSP1‐1.9 and SSP1‐2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1‐H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5‐8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1‐G (−1.21 × 106 km2/°C) and E2.1‐H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5‐8.5 in the E2.1‐G model, comparable to the reduction in the corresponding CMIP5 GISS‐E2 RCP8.5 simulation. Both low‐end scenarios SSP1‐1.9 and SSP1‐2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century).

The Earth Model Column Collaboratory (EMC<sup>2</sup>) v1.1: an open-source ground-based lidar and radar instrument simulator and subcolumn generator for large-scale models

Abstract. Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars, and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.

Evolution of Tropical Cyclone Properties Across the Development Cycle of the GISS-E3 Global Climate Model.

The next‐generation global climate model from the NASA Goddard Institute for Space Studies, GISS‐E3, contains many improvements to resolution and physics that allow for improved representation of tropical cyclones (TCs) in the model. This study examines the properties of TCs in two different versions of E3 at different points in its development cycle, run for 20 years at 0.5° resolution, and compares these TCs with observations, the previous generation GISS model, E2, and other climate models. E3 shares many TC biases common to global climate models, such as having too few tropical cyclones, but is much improved from E2. E3 produces strong enough TCs that observation‐based wind speed thresholds can now be used to detect and track them, and some storms now reach hurricane intensity; neither of these was true of E2. Model development between the first and second versions of E3 further increased the number and intensity of TCs and reduced TC count biases globally and in most regions. One‐year sensitivity tests to changes in various microphysical and dynamical tuning parameters are also examined. Increasing the entrainment rate for the more strongly entraining plume in the convection scheme increases the number of TCs (though also affecting other climate variables, and in some cases increasing biases). Variations in divergence damping did not have a strong effect on simulated TC properties, contrary to expectations based on previous studies. Overall, the improvements in E3 make it more credible for studies of TC activity and its relationship to climate.

CURRENT UNDERSTANDING OF THE MECHANISMS OF HEAT STRESS TOLERANCE IN RICE (Oryza sativa L.)

Various studies reported by scientific communities such as NASA’s Goddard Institute for Space Studies (GISS) indicated an increase in average global temperature by approx. 0.8 °C since 1880. Rice (Oryza sativa L.), a heat sensitive plant cereal crop could be greatly affected by heat stress due to global temperature rise. Thus, it is envisaged that rice productivity could markedly decrease due to a rise in mean atmospheric temperature. Different studies have been reported possible mechanisms of heat stress tolerance in Rice. The present review will therefore discuss the current fundamental understanding of heat tolerant mechanisms involving heat shock proteins, plant hormones, plant growth regulators, osmoprotectants, and the importance of membrane thermal stability in rice.

GCAP 2.0: a global 3-D chemical-transport model framework for past, present, and future climate scenarios

Abstract. This paper describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the pre-industrial era and the recent past. In addition, meteorology is available for the near future and end of the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport, and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) product and with observational constraints.