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NASA NTRS2020

The GGCMI Phase 2 Experiment: Global Gridded Crop Model Simulations Under Uniform Changes in CO2, Temperature, Water, and Nitrogen Levels (Protocol Version 1.0)

Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen (“CTWN”) for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.

GGCMI↗
NASA NTRS2010

Applied Meteorology Unit (AMU) Quarterly Report

By providing a global view with a level playing field (no region missed because of unfavorable surface conditions or political boundaries), satellites have made major contributions to improved monitoring and understanding of our constantly changing planet. The global view has allowed surprising realizations like the relative sparsity of lightning strikes over oceans and the large-scale undulations on the massive Antarctic ice sheet. It has allowed the tracking of all sorts of phenomena, including aerosols, both natural and anthropogenic,as they move with the atmospheric circulation and impact weather and human health. But probably nothing that the global view allows is more important in the long term than its provision of unbiased data sets to address the issue of global change, considered by many to be among the most important issues facing humankind today. With satellites we can monitor atmospheric temperatures at all latitudes and longitudes, and obtain a global average that lessens the likelihood of becoming endlessly mired in the confusions brought about by the certainty of regional differences. With satellites we can monitor greenhouse gases such as CO2 not just above individual research stations but around the globe. With satellites we can monitor the polar sea ice covers, as we have done since the late 1970s, determining and quantifying the significant reduction in Arctic sea ice and the slight growth in Antarctic sea ice over that period. With satellites we can map the full extent and changes in the Antarctic stratospheric ozone depletions that were first identified from a single ground station; and through satellite data we have witnessed from afar land surface changes brought about by humans both intentionally, as with wide-scale deforestation, and unintentionally, as with the decay of the Aral Sea. The satellite data are far from sufficient for all that we need in order to understand the global system and forecast its changes, as we also need sophisticated climate models, in situ process studies, and data sets that extend back well before the introduction of satellite technology. Nuomthc)cmm, the repetitive, global view provided by satellites is contributing in a major way to our improved recognition of how the Earth is changing, a recognition that is none too soon in view of the magnitude of the impacts that humans can now have.

Bauman, William↗
NASA NTRS2013

A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

For the first time, a formal comparison is made between gravity wave momentum fluxes in models and those derived from observations. Although gravity waves occur over a wide range of spatial and temporal scales, the focus of this paper is on scales that are being parameterized in present climate models, sub-1000-km scales. Only observational methods that permit derivation of gravity wave momentum fluxes over large geographical areas are discussed, and these are from satellite temperature measurements, constant-density long-duration balloons, and high-vertical-resolution radiosonde data. The models discussed include two high-resolution models in which gravity waves are explicitly modeled, Kanto and the Community Atmosphere Model, version 5 (CAM5), and three climate models containing gravity wave parameterizations,MAECHAM5, Hadley Centre Global Environmental Model 3 (HadGEM3), and the Goddard Institute for Space Studies (GISS) model. Measurements generally show similar flux magnitudes as in models, except that the fluxes derived from satellite measurements fall off more rapidly with height. This is likely due to limitations on the observable range of wavelengths, although other factors may contribute. When one accounts for this more rapid fall off, the geographical distribution of the fluxes from observations and models compare reasonably well, except for certain features that depend on the specification of the nonorographic gravity wave source functions in the climate models. For instance, both the observed fluxes and those in the high-resolution models are very small at summer high latitudes, but this is not the case for some of the climate models. This comparison between gravity wave fluxes from climate models, high-resolution models, and fluxes derived from observations indicates that such efforts offer a promising path toward improving specifications of gravity wave sources in climate models.

mathematical models↗
NASA NTRSDate not supplied

NASA Earth Exchange – Current overview of climate and wildfire-oriented works

NASA Earth Exchange (NEX) combines state-of-the-art supercomputing, Earth system modeling, and NASA remote sensing data feeds to deliver a work environment for exploring and analyzing petabyte-scale datasets covering large regions, continents, or the globe. As an accessible platform, NEX can accelerate fundamental research, develop new applications, and reduce overall project costs by providing the research community with data, software, and high-end computing power. Two research thrusts for the NEX community are developing and distributing the NEX-GDDP-CMIP6 downscaled climate dataset and the community-driven wildfire research. NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The wildfire research thrust leverages geostationary and low earth orbit remote sensing platforms and advanced modeling (WRF). We present a high-level overview of the NEX community, discuss relevant datasets and show several visualization techniques of data used in the wildfire research activity.

NEX↗
DOE OSTI2023

Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model

Abstract. Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales (MPAS; dynamical core version 4.0) coupled to the Community Atmosphere Model (CAM; version 5.4), which we refer to as CAM–MPAS hereafter. This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM–MPAS downscaling data. The CAM–MPAS model is configured with VR meshes featuring higher resolutions over North America as well as quasi-uniform-resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea-ice changes from the low-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-LR) in the Coupled Model Intercomparison Project Phase 5 to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the midlatitude circulations in the Northern Hemisphere, including the downscaling target of North America. The pseudo-warming experiment leads to similar responses of large-scale circulations to the imposed radiative and boundary forcings in the CAM–MPAS and MPI-ESM-LR models, but their climatological states in the historical period differ over various regions, including North America. Such differences are carried to the future period, suggesting the importance of the base state climatology. Within the refined domain, precipitation statistics improve with higher resolutions, and such statistical inference is verified to be negligibly influenced by horizontal remapping during post-processing. Limited (≈50 % slower) throughput of the current code is found on a recent many-core/wide-vector high-performance computing system, which limits the lengths of the 12–46 km simulations and indirectly affects sampling uncertainty. Our experience shows that global and technical aspects of the VR downscaling framework require further investigations to reduce uncertainties for regional climate projection.

58 GEOSCIENCES↗
NASA NTRS1997

Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction.

Yang, Runhua↗
DOE OSTI2025

Boundary-Layer-Coupled and Decoupled Clouds in Global Storm-Resolving Models: Comparisons With the ARM Observations

The accurate representation of interactions between clouds and planetary boundary layer (PBL) is a persistent challenge in climate models, critical for simulating surface energy budget. The emergence of kilometer-grid-scale global storm resolving models (GSRMs) offers the potential for enhanced details of PBL processes in these complex interactions. This study evaluates the representation of PBL-coupled and decoupled clouds in nine GSRM simulations against extensive ground-based observations by the Department of Energy Atmospheric Radiation Measurement (ARM) program, across six sites encompassing diverse regimes such as marine and continental environments in tropics and midlatitude. By differentiating coupling based on the relative positions between cloud bases and PBL tops, our analysis focuses on the simulation of PBL height, cloud frequency, position and vertical extent. The GSRMs generally exhibit commendable agreements with observed cloud structures and PBL diurnal cycles across different ARM sites. In contrast to the relatively consistent representation of decoupled clouds, discrepancies exist between the simulated and the observed coupled clouds, particularly in areas of intense convection, for example, over tropical rainforests and mountainous regions. These biases are probably associated with the models' tendency to underestimate the boundary layer humidity and the frequency of coupled clouds within different ranges of PBL heights. This study underscores the importance for continuous improvements in the representation of boundary layer and convection within these global kilometer-grid-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The Value of Reversible Carbon Storage in a Zero-Emissions World

Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.

carbon capture and storage↗
NASA NTRS2012

A Canonical Response in Rainfall Characteristics to Global Warming: Projections by IPCC CMIP5 Models

Changes in rainfall characteristics induced by global warming are examined based on probability distribution function (PDF) analysis, from outputs of 14 IPCC (Intergovernmental Panel on Climate Change), CMIP (5th Coupled Model Intercomparison Project) models under various scenarios of increased CO2 emissions. Results show that collectively CMIP5 models project a robust and consistent global and regional rainfall response to CO2 warming. Globally, the models show a 1-3% increase in rainfall per degree rise in temperature, with a canonical response featuring large increase (100-250 %) in frequency of occurrence of very heavy rain, a reduction (5-10%) of moderate rain, and an increase (10-15%) of light rain events. Regionally, even though details vary among models, a majority of the models (>10 out of 14) project a consistent large scale response with more heavy rain events in climatologically wet regions, most pronounced in the Pacific ITCZ and the Asian monsoon. Moderate rain events are found to decrease over extensive regions of the subtropical and extratropical oceans, but increases over the extratropical land regions, and the Southern Oceans. The spatial distribution of light rain resembles that of moderate rain, but mostly with opposite polarity. The majority of the models also show increase in the number of dry events (absence or only trace amount of rain) over subtropical and tropical land regions in both hemispheres. These results suggest that rainfall characteristics are changing and that increased extreme rainfall events and droughts occurrences are connected, as a consequent of a global adjustment of the large scale circulation to global warming.

Lau, William K. M.↗
DOE OSTI2022

Threat by marine heatwaves to adaptive large marine ecosystems in an eddy-resolving model

Marine heatwaves (MHWs), episodic periods of abnormally high sea surface temperature, severely affect marine ecosystems. Large marine ecosystems (LMEs) cover ~22% of the global ocean but account for 95% of global fisheries catches. Yet how climate change affects MHWs over LMEs remains unknown because such LMEs are confined to the coast where low-resolution climate models are known to have biases. Here, using a high-resolution Earth system model and applying a ‘future threshold’ that considers MHWs as anomalous warming above the long-term mean warming of sea surface temperatures, we find that future intensity and annual days of MHWs over the majority of the LMEs remain higher than in the present-day climate. Better resolution of ocean mesoscale eddies enables simulation of more realistic MHWs than low-resolution models. These increases in MHWs under global warming pose a serious threat to LMEs, even if resident organisms could adapt fully to the long-term mean warming.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Changes in Extratropical Storm Track Cloudiness 1983-2008: Observational Support for a Poleward Shift

Climate model simulations suggest that the extratropical storm tracks will shift poleward as a consequence of global warming. In this study the northern and southern hemisphere storm tracks over the Pacific and Atlantic ocean basins are studied using observational data, primarily from the International Satellite Cloud Climatology Project, ISCCP. Potential shifts in the storm tracks are examined using the observed cloud structures as proxies for cyclone activity. Different data analysis methods are employed, with the objective to address difficulties and uncertainties in using ISCCP data for regional trend analysis. In particular, three data filtering techniques are explored; excluding specific problematic regions from the analysis, regressing out a spurious viewing geometry effect, and excluding specific cloud types from the analysis. These adjustments all, to varying degree, moderate the cloud trends in the original data but leave the qualitative aspects of those trends largely unaffected. Therefore, our analysis suggests that ISCCP data can be used to interpret regional trends in cloudiness, provided that data and instrumental artefacts are recognized and accounted for. The variation in magnitude between trends emerging from application of different data correction methods, allows us to estimate possible ranges for the observational changes. It is found that the storm tracks, here represented by the extent of the midlatitude-centered band of maximum cloud cover over the studied ocean basins, experience a poleward shift as well as a narrowing over the 25 year period covered by ISCCP. The observed magnitudes of these effects are larger than in current generation climate models (CMIP3). The magnitude of the shift is particularly large in the northern hemisphere Atlantic. This is also the one of the four regions in which imperfect data primarily prevents us from drawing firm conclusions. The shifted path and reduced extent of the storm track cloudiness is accompanied by a regional reduction in total cloud cover. This decrease in cloudiness can primarily be ascribed to low level clouds, whereas the upper level cloud fraction actually increases, according to ISCCP. Independent satellite observations of radiative fluxes at the top of the atmosphere are consistent with the changes in total cloud cover. The shift in cloudiness is also supported by a shift in central position of the mid-troposphere meridional temperature gradient. We do not find support for aerosols playing a significant role in the satellite observed changes in cloudiness. The observed changes in storm track cloudiness can be related to local cloud-induced changes in radiative forcing, using ERBE and CERES radiative fluxes. The shortwave and the longwave components are found to act together, leading to a positive (warming) net radiative effect in response to the cloud changes in the storm track regions, indicative of positive cloud feedback. Among the CMIP3 models that simulate poleward shifts in all four storm track areas, all but one show decreasing cloud amount on a global mean scale in response to increased CO2 forcing, further consistent with positive cloud feedback. Models with low equilibrium climate sensitivity to a lesser extent than higher-sensitivity models simulate a poleward shift of the storm tracks.

Bender, Frida A-M.↗
NASA NTRS2010

A Global Modeling Study on Carbonaceous Aerosol Microphysical Characteristics and Radiative Effects

Recently, attention has been drawn towards black carbon aerosols as a short-term climate warming mitigation candidate. However the global and regional impacts of the direct, indirect and semi-direct aerosol effects are highly uncertain, due to the complex nature of aerosol evolution and the way that mixed, aged aerosols interact with clouds and radiation. A detailed aerosol microphysical scheme, MATRIX, embedded within the GISS climate model is used in this study to present a quantitative assessment of the impact of microphysical processes involving black carbon, such as emission size distributions and optical properties on aerosol cloud activation and radiative effects. Our best estimate for net direct and indirect aerosol radiative flux change between 1750 and 2000 is -0.56 W/m2. However, the direct and indirect aerosol effects are quite sensitive to the black and organic carbon size distribution and consequential mixing state. The net radiative flux change can vary between -0.32 to -0.75 W/m2 depending on these carbonaceous particle properties at emission. Taking into account internally mixed black carbon particles let us simulate correct aerosol absorption. Absorption of black carbon aerosols is amplified by sulfate and nitrate coatings and, even more strongly, by organic coatings. Black carbon mitigation scenarios generally showed reduced radiative fluxeswhen sources with a large proportion of black carbon, such as diesel, are reduced; however reducing sources with a larger organic carbon component as well, such as bio-fuels, does not necessarily lead to a reduction in positive radiative flux.

Bauer, S. E.↗
NASA NTRS1992

Topex/Poseidon: A United States/France mission. Oceanography from space: The oceans and climate

The TOPEX/POSEIDON space mission, sponsored by NASA and France's space agency, the Centre National d'Etudes Spatiales (CNES), will give new observations of the Earth from space to gain a quantitative understanding of the role of ocean currents in climate change. Rising atmospheric concentrations of carbon dioxide and other 'greenhouse gases' produced as a result of human activities could generate a global warming, followed by an associated rise in sea level. The satellite will use radar altimetry to measure sea-surface height and will be tracked by three independent systems to yield accurate topographic maps over the dimensions of entire ocean basins. The satellite data, together with the Tropical Ocean and Global Atmosphere (TOGA) program and the World Ocean Circulation Experiment (WOCE) measurements, will be analyzed by an international scientific team. By merging the satellite observations with TOGA and WOCE findings, the scientists will establish the extensive data base needed for the quantitative description and computer modeling of ocean circulation. The ocean models will eventually be coupled with atmospheric models to lay the foundation for predictions of global climate change.

Source record↗
NASA NTRS2011

Global Land Surface Emissivity Retrieved From Satellite Ultraspectral IR Measurements

Ultraspectral resolution infrared (IR) radiances obtained from nadir observations provide information about the atmosphere, surface, aerosols, and clouds. Surface spectral emissivity (SSE) and surface skin temperature from current and future operational satellites can and will reveal critical information about the Earth s ecosystem and land-surface-type properties, which might be utilized as a means of long-term monitoring of the Earth s environment and global climate change. In this study, fast radiative transfer models applied to the atmosphere under all weather conditions are used for atmospheric profile and surface or cloud parameter retrieval from ultraspectral and/or hyperspectral spaceborne IR soundings. An inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral IR sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface or cloud microphysical parameters. This inversion scheme has been applied to the Infrared Atmospheric Sounding Interferometer (IASI). Rapidly produced SSE is initially evaluated through quality control checks on the retrievals of other impacted surface and atmospheric parameters. Initial validation of retrieved emissivity spectra is conducted with Namib and Kalahari desert laboratory measurements. Seasonal products of global land SSE and surface skin temperature retrieved with IASI are presented to demonstrate seasonal variation of SSE.

Zhou, D. K.↗
NASA NTRS2001

Tropical Oceanic Precipitation Processes Over Warm Pool: 2D and 3D Cloud Resolving Model Simulations

Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere. The vertical distribution of convective latent-heat release modulates the large-scale circulations of the topics. Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate model simulate processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMs) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and clouds systems. The major objective of this paper is to investigate the latent heating, moisture and momentum budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (GCE) model which includes a 3-class ice-phase microphysics scheme.

Tao, W.-K.↗
NASA NTRS2017

Towards a New Food System Assessment: AgMIP Coordinated Global and Regional Assessments of Climate Change

Agricultural stakeholders need more credible information on which to base adaptation and mitigation policy decisions. In order to provide this, we must improve the rigor of agricultural modelling. Ensemble approaches can be used to address scale issues and integrated teams can overcome disciplinary silos. The AgMIP Coordinated Global and Regional Assessments of Climate Change and Food Security (CGRA) has the goal to link agricultural systems models using common protocols and scenarios to significantly improve understanding of climate effects on crops, livestock and livelihoods across multiple scales. The AgMIP CGRA assessment brings together experts in climate, crop, livestock, economics, and food security to develop Protocols to guide the process throughout the assessment. Scenarios are designed to consistently combine elements of intertwined storylines of future society including, socioeconomic development, greenhouse gas concentrations, and specific pathways of agricultural sector development. Through these approaches, AgMIP partners around the world are providing an evidence base for their stakeholders as they make decisions and investments.

Ensembles↗
NASA NTRS2020

Hiatus of wetland methane emissions associated with recent La Niña episodes in the Asian monsoon region

The variability of methane emissions from wetlands in the tropics and northern temperate regions can explain more than 70% of the interannual variation in global wetland methane emissions, which are largely driven by climate variability. We use climate reanalysis, remote sensing wetland area dataset and simulations from 11 land models contributing to Global Methane Budget to investigate the interannual variation and anomalies of wetland methane emissions in the Asian Monsoon region. Methane emissions in this region steadily increased over 2000–2012. However, abnormally low methane emissions were found in equatorial fully humid (Af), warm temperate winter dry (Cw), and warm temperate fully humid (Cf) Asian Monsoon climate sub-regions in 2008, 2009 and 2011, respectively. These spatially-shifting low emissions occurred simultaneously with observed wetland area shrinkage due to abnormally low precipitation. Interannual variability of wetland methane emissions in Asian Monsoon region are primarily driven by South Asian Monsoon system. However, the abnormally low emissions are related to strong La Niña events, and its accompanying effect of weakened East Asian Monsoon system and eastward Western Pacific subtropical high, which drives the shifting pattern of rainfall, and thus the spatial pattern of methane emission anomalies.

wetlands↗
NASA NTRS2021

Tropical Cyclones in Global Storm-Resolving Models

Recent progress in computing and model development has initiated the era of global storm-resolving modeling, and with it the potential to transform weather and climate prediction. Within the general theme of vetting this new class of models, the present study evaluates nine global-storm resolving models in their ability to simulate tropical cyclones (TCs). Results indicate that, broadly speaking, the models produce realistic TCs and remove longstanding issues known from global models such as the deficiency in accurately simulating TC intensity. However, TCs are strongly affected by model formulation, and all models suffer from unique biases regarding the number of TCs, intensity, size, and structure. Some models simulated TCs better than others, but no single model was superior in every way. The overall results indicate that global storm-resolving models can open a new chapter in TC prediction, but they need to be improved to unleash their full potential.

Falko Judt↗