Precipitation measurement requirements for general circulation climate model development and applications
Global scale diagnostics, regional diagnostics, and satellite IR data are discussed.
Mintz, Y.↗
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Advances in Understanding Decadal Climate Variability
Recently, a joint Brazil-France-U.S. program, known as PIRATA (Pilot Research moored Array in the Tropical Atlantic), was proposed to begin the deployment of moored measurement platforms in the tropical Atlantic in order to enhance the existing observational data base and subsequent understanding of the processes by which the ocean and atmosphere couple in key regions of the tropical Atlantic Ocean. Empirical studies have suggested that there are strong relationships between tropical Atlantic upper ocean variability, SST, ocean-atmosphere coupling and regional climate variability. During the early 1980's a coordinated set of surface wind, subsurface thermal structure, and subsurface current observations were obtained as part of the U.S.-France SEQUAL-FOCAL process experiment designed to observe the seasonal response of the tropical Atlantic Ocean to surface forcing. Since that time, however, the observational data base for the tropical Atlantic Ocean has disintegrated to a few ship-tracks measuring ocean temperatures and a small collection of tide gauge stations measuring sea level. A more comprehensive set of observations, modeling and empirical studies is now in order to make progress on understanding the regional climate variability. The proposed PIRATA program will use mooring platforms similar to the tropical Pacific Ocean TAO array to measure surface fluxes of momentum and heat and the corresponding changes in the upper ocean thermal structure. It is anticipated that the oceanic data from this monitoring array will also be used in a predictive mode for initialization studies of regional coupled climate models. Of particular interest are zonal and meridional modes of ocean-atmosphere variability within the tropical Atlantic basin that have significant impacts on the regional climate of the bordering continents.
Busalacchi, Antonio J.↗
Climatic Effects of Regional Nuclear War
We use a modern climate model and new estimates of smoke generated by fires in contemporary cities to calculate the response of the climate system to a regional nuclear war between emerging third world nuclear powers using 100 Hiroshima-size bombs (less than 0.03% of the explosive yield of the current global nuclear arsenal) on cities in the subtropics. We find significant cooling and reductions of precipitation lasting years, which would impact the global food supply. The climate changes are large and longlasting because the fuel loadings in modern cities are quite high and the subtropical solar insolation heats the resulting smoke cloud and lofts it into the high stratosphere, where removal mechanisms are slow. While the climate changes are less dramatic than found in previous "nuclear winter" simulations of a massive nuclear exchange between the superpowers, because less smoke is emitted, the changes seem to be more persistent because of improvements in representing aerosol processes and microphysical/dynamical interactions, including radiative heating effects, in newer global climate system models. The assumptions and calculations that go into these conclusions will be described.
Oman, Luke D.↗
Solar Forcing of Regional Climate Change During the Maunder Minimum
We examine the climate response to solar irradiance changes between the late 17th century Maunder Minimum and the late 18th century. Global average temperature changes are small (about 0.3 to 0.4 C) in both a climate model and empirical reconstructions. However, regional temperature changes are quite large. In the model, these occur primarily through a forced shift toward the low index state of the Arctic Oscillation/North Atlantic Oscillation. This leads to colder temperatures over the Northern Hemisphere continents, especially in winter (1 to 2 C), in agreement with historical records and proxy data for surface temperatures.
Shindell, Drew T.↗
Regional Warming from Aerosol Removal over the United States: Results from a Transient 2010-2050 Climate Simulation
We use a general circulation model (NASA Goddard Institute for Space Studies GCM 3) to investigate the regional climate response to removal of aerosols over the United States. We perform a pair of transient 2010e2050 climate simulations following a scenario of increasing greenhouse gas concentrations, with and without aerosols over the United States and with present-day aerosols elsewhere. We find that removing U.S. aerosol significantly enhances the warming from greenhouse gases in a spatial pattern that strongly correlates with that of the aerosol. Warming is nearly negligible outside the United States, but annual mean surface temperatures increase by 0.4e0.6 K in the eastern United States. Temperatures during summer heat waves in the Northeast rise by as much as 1e2 K due to aerosol removal, driven in part by positive feedbacks involving soil moisture and low cloud cover. Reducing U.S. aerosol sources to achieve air quality objectives could thus have significant unintended regional warming consequences.
Mickley, L. J.↗
Environmental impact of national and subnational carbon policies in China based on a multi-regional dynamic CGE model
Carbon policies are important not only for mitigating global climate change, but also for controlling local and regional air pollution. The large regional disparities in economic development and air pollution across China calls for regionally differentiated policies. Previous studies have not systematically investigated the environmental impacts of regional carbon policies in China covering different spatial scales. This study constructs a multi-regional dynamic computable general quilibrium (CGE) model covering 30 provinces of China to assess the impacts of national and subnational carbon polices on CO2 emissions and co-emitted air pollutants from 2020 to 2050. We consider one national carbon policy which aims to achieve China’s 2030 national CO2 abatement target, as well as three regional policies with the same policy stringency as the national one but only applied to eastern China (EP), the Jiangsu-Shanghai-Zhejiang area (JSZP), and the Beijing-Tianjin-Hebei area (BTHP), respectively. We find that regional policies (EP, JSZP, and BTHP) are as effective in reducing CO2 emissions in their targeted regions as the national policy. However, they lead to an increase in CO2 emissions in untargeted regions (the so-called “emissions leakage”). The CO2 leakage rates, which depend on the policy spatial coverage, are 4%, 13%, and 65% for EP, JSZP, and BTHP, respectively, in 2050. Compared with CO2, changes in air pollutant emissions, including sulfur dioxide (SO2), nitrogen oxides (NOx), volatile organic compounds (VOC), and fine particulate matter (PM2.5), exhibit a similar pattern under all policy scenarios, but the magnitude of change is significantly smaller. Transportation, thermal power, and some energy intensive industries are the three largest contributors to CO2 and air pollutant emission reductions. Our results suggest that regional carbon policy is effective in reducing CO2 and air pollutant emissions in the targeted regions, and extending the spatial coverage or increasing policy stringency can largely inhibit emissions leakage.
Zhang, Wenwen↗
Compound Effects of Climate Change on Future Transboundary Water Issues in the Middle East
The Middle East is one of the world’s most vulnerable areas to climate change, which has exacerbated environmental, agricultural, water conflict, and public health issues in the region. Here we analyze the latest climate model projections of precipitation and temperature for the very high emissions scenario, SSP5-8.5,to detect potential future changes in this region. A baseline period (1981-2010) is compared with the middle(2040-2069) and end (2070-2099) of the 21stcentury. The results, representing the worst-case scenario, identify the Tigris-Euphrates headwaters as the hotspot of future compounding effects of climate change in the Middle East. Those effects result from the coincidence of elevated temperature, reduced precipitation, and enhanced interannual variability of precipitation. The hotspot overlays the location of the Southeastern Anatolia Project (in Turkish, GAP) irrigation initiative. In this climate context, risks to GAP viability and downstream water security, and associated potential for water-related conflicts and migration are considerable and demand a reconsideration of the risk-benefit assessment of GAP. This need has become more urgent after the recent widespread and deadly climate-related conflicts and wildfires in summer 2021 across the Middle East that further underlined vulnerability of the region to climate extremes.
Tigris-Euphrates headwater↗
Evaluating models of climate and forest vegetation
Understanding how the biosphere may respond to increasing trace gas concentrations in the atmosphere requires models that contain vegetation responses to regional climate. Most of the processes ecologists study in forests, including trophic interactions, nutrient cycling, and disturbance regimes, and vital components of the world economy, such as forest products and agriculture, will be influenced in potentially unexpected ways by changing climate. These vegetation changes affect climate in the following ways: changing C, N, and S pools; trace gases; albedo; and water balance. The complexity of the indirect interactions among variables that depend on climate, together with the range of different space/time scales that best describe these processes, make the problems of modeling and prediction enormously difficult. These problems of predicting vegetation response to climate warming and potential ways of testing model predictions are the subjects of this chapter.
Clark, James S.↗
A Simple Lagrangian Parcel Model for the Initiation of Summer-time Mesoscale Convective Systems over the Central United States
Mesoscale convective systems (MCSs) account for more than 50% of summertime precipitation over the central United States and have a significant impact on local weather and hydrologic cycle. It is hypothesized that the inadequate treatment of MCSs is responsible for the long-standing warm and dry bias over the central United States in coarse-resolution general circulation model (GCM) simulations. In particular, a better understanding of MCS initiation is still lacking. Here a single-column Lagrangian parcel model is first developed to simulate the basic features of a rising parcel. This simple model demonstrates the collective effects of boundary layer moistening and dynamical lifting in triggering convective initiation and reproduces successfully its early afternoon peak with surface equivalent potential temperature as a controlling factor. It also predicts that convection is harder to trigger in the future climate under global warming, consistent with the results from convection-permitting regional climate simulations. Then, a multicolumn model that includes an array of single-column models aligned in the east–west direction and incorporates idealized cold pool interaction mechanisms is developed. The multicolumn model captures readily the cold pool–induced upscale growth feature in MCS genesis from initially scattered convection that is organized into a mesoscale cluster in a few hours. It also highlights the crucial role of lifting effects due to cold pool collision and spreading, subsidence effect, and gust front propagation speed in controlling the final size of mesoscale clusters and cold pool regions. This simple model should be useful for understanding fundamental mechanisms of MCS initiation and providing guidance for improving MCS simulations in GCMs.
54 ENVIRONMENTAL SCIENCES↗
Metrics for Improved Reanalyses in Polar Regions
Atmospheric reanalyses are widely used for a variety of scientific endeavors in the Arctic and Antarctic. Reanalyses are used as boundary conditions for a regional and process-based models, for climate model validation, and for diagnostic analysis of physical processes, weather and climatic events. However, reanalyses are typically global and often do not account for specific, regional considerations, such as for polar regions. In this work, we provide a brief evaluation of a prototype for a new GMAO reanalysis, which incorporates higher spatial resolution, an updated approach for data assimilation, and a revised atmospheric model. We identify differences in the representation of the Arctic atmosphere in comparison to recent reanalyses. Furthermore, we provide a forum for Arctic scientists to consider the future improvements for reanalyses, and seek feedback for the following questions: 1) What are important performance factors to consider in evaluating new reanalyses? 2) What physical processes should be incorporated into new reanalyses? 3) What spatio-temporal scales should be considered?
Parker, Chelsea L.↗
Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM
Model simulations of global climate change are seen as an essential component of any program aimed at understanding human impact on the global environment. A major weakness of current general circulation models (GCMs), however, is their inability to predict reliably the regional consequences of a global scale change, and it is these regional scale predictions that are necessary for studies of human/environmental response. This research is directed toward the development of a methodology for the validation of the synoptic scale climatology of GCMs. This is developed with regard to the Goddard Institute for Space Studies (GISS) GCM Model 2, with the specific objective of using the synoptic circulation form a doubles CO2 simulation to estimate regional climate change over North America, south of Hudson Bay. This progress report is specifically concerned with validating the synoptic climatology of the GISS GCM, and developing the transfer function to derive grid-point temperatures from the synoptic circulation. Principal Components Analysis is used to characterize the primary modes of the spatial and temporal variability in the observed and simulated climate, and the model validation is based on correlations between component loadings, and power spectral analysis of the component scores. The results show that the high resolution GISS model does an excellent job of simulating the synoptic circulation over the U.S., and that grid-point temperatures can be predicted with reasonable accuracy from the circulation patterns.
Crane, Robert G.↗
The Fall and Rise of the Global Climate Model
Abstract Global models are an essential tool for climate projections, but conventional coarse‐resolution atmospheric general circulation models suffer from errors both in their parameterized cloud physics and in their representation of climatically important circulation features. A notable recent study by Terai et al. (2020, https://doi.org/10.1029/2020ms002274) documents a global model capable of reproducing the regime‐based effect of aerosols on cloud liquid water path expected from observational evidence. This may represent a significant advance in cloud process fidelity in global models. Such models can be expected to give a better estimate of the effective radiative forcing of the climate. If this advance in cloud process representation can be matched by advances in the representation of circulation features such as monsoons, then such models may also be able to navigate the complex tangle between spatially heterogeneous aerosol–cloud interactions and regional circulation patterns. This tight link between aerosol and circulation results in anthropogenic perturbations of climate variables of societal importance, such as regional rainfall distributions. Upcoming global models with km‐scale resolution may improve the regional circulation and be able to take advantage of the Terai et al. (2020, https://doi.org/10.1029/2020ms002274) improvement in cloud physics. If so, an era of significantly improved regional climate projection capabilities may soon dawn. If not, then the improvement in cloud physics might spur intensified efforts on problems in model dynamics. Either way, based on the rapid changes in aerosol emissions in the near future, learning to make reliable projections based on biased models is a skill that will not go out of style.
54 ENVIRONMENTAL SCIENCES↗
Satellite-Derived Water Vapor Winds for Regional Climate Studies
The retrieval of winds and humidity in the upper-troposphere has matured to the point where it may now be possible to better understand and diagnose regional climate variations from geostationary satellites than from conventional measurements or model analysis, especially in data sparse regions. In this poster paper, upper-tropospheric circulation features and moisture transport covering ENSO periods are presented and discussed. Precursor and other detectable interannual climate signals are analyzed and compared to model diagnosed features. Estimates of winds and humidity over data-rich regions (from conventional measurements) are used to show the robustness of the data and its value over regions which are currently poorly sampled.
Jedlovce, Gary J.↗
An assessment of tropical cyclones in North American $\mathrm{CORDEX}$ $\mathrm{WRF}$ simulations
This work presents an assessment of tropical cyclones (TCs) in the 25 km and 50 km resolution reanalysis-forced and baseline and future (RCP8.5) global climate model (GCM) forced simulations produced for the North American branch of the international Coordinated Regional climate Downscaling Experiment (NA-CORDEX) using the Weather Research and Forecasting (WRF) model. A set of complementary 12 km resolution simulations produced as a part of a different project is also included in this assessment. Before examining the projections from the GCM-driven simulations, the ability of the simulations to minimally produce a realistic spatial distribution of historical TC occurrence was assessed in simulations forced by reanalysis and the three different GCMs used herein. Then, projections for occurrence, TC related mean precipitation and precipitation intensity, storm duration, the intensity measured by minimum pressure and maximum wind speed, storm size, and translation speed were examined. Several of these characteristics show little to no change in the future in trend or in distribution across the ensemble. However, many simulations suggest a westward shift or increase in TC occurrence over the East Pacific basin and a decrease in occurrence over the Caribbean and Gulf of Mexico. Increases (decreases) in total storm-related precipitation are projected where TC occurrence increases (decreases). TC precipitation intensity is found to increase in all simulations over the East Pacific, but projections are mixed over the North Atlantic. Finally, the ensemble projects a distribution shift towards more intense TC over the East Pacific, and a shift toward faster translation speeds over the North Atlantic.
54 ENVIRONMENTAL SCIENCES↗
Modeling Feedbacks Between Water and Vegetation in the Climate System
Not only is water essential for life on earth, but life itself affects the global hydrologic cycle and consequently the climate of the planet. Whether the global feedbacks between life and the hydrologic cycle tend to stabilize the climate system about some equilibrium level is difficult to assess. We use a global climate model to examine how the presence of vegetation can affect the hydrologic cycle in a particular region. A control for the present climate is compared with a model experiment in which the Sahara Desert is replaced by vegetation in the form of trees and shrubs common to the Sahel region. A second model experiment is designed to identify the separate roles of two different effects of vegetation, namely the modified albedo and the presence of roots that can extract moisture from deeper soil layers. The results show that the presence of vegetation leads to increases in precipitation and soil moisture in western Sahara. In eastern Sahara, the changes are less clear. The increase in soil moisture is greater when the desert albedo is replaced by the vegetation albedo than when both the vegetation albedo and roots are added. The effect of roots is to withdraw water from deeper layers during the dry season. One implication of this study is that the insertion of vegetation into the Sahara modifies the hydrologic cycle so that the vegetation is more likely to persist than initially.
Miller, James R.↗
Identifying Climate Patterns Using Clustering Autoencoder Techniques
Abstract The complexity of growing spatiotemporal resolution of climate simulations produces a variety of climate patterns under different projection scenarios. This paper proposes a new data-driven climate classification workflow via an unsupervised deep learning technique that can dimensionally reduce the vast volume of spatiotemporal numerical climate projection data into a compact representation. We aim to identify distinct zones that capture multiple climate variables as well as their future changes under different climate change scenarios. Our approach leverages convolutional autoencoders combined with k -means clustering (standard autoencoder) and online clustering based on the Sinkhorn–Knopp algorithm (clustering autoencoder) across the conterminous United States (CONUS) to capture unique climate patterns in a data-driven fashion from the Geophysical Fluid Dynamics Laboratory Earth System Model with GOLD component (GFDL-ESM2G). The developed approach compresses 70 years of GFDL-ESM2G simulation at 0.125° spatial resolution across the CONUS under multiple warming scenarios to a lower-dimensional space by a factor of 660 000 and then tested on 150 years of GFDL-ESM2G simulation data. The results show that five climate clusters capture physically reasonable and spatially stable climatological patterns matched to known climate classes defined by human experts. Results also show that using a clustering autoencoder can reduce the computational time for clustering by up to 9.2 times when compared to using a standard autoencoder. Our five unique climate patterns resulting from the deep learning–based clustering of the lower-dimensional space thereby enable us to provide insights on hydrometeorology and its spatial heterogeneity across the conterminous United States immediately without downloading large climate datasets. Significance Statement This paper presents a data-driven climate classification approach using unsupervised deep learning to dimensionally reduce climate model outputs and to identify distinct climate regions for their future changes. Our approach compresses climate information for 70 years of Geophysical Fluid Dynamics Laboratory Earth System Model data across the conterminous United States (CONUS) at 0.125° spatial resolution. The results reveal that five climate clusters capture reasonable and stable climatological patterns matched to known climate patterns. The embedded clustering process in deep learning provides ×9.2 times faster execution than the k -means clustering technique. These results give us insight about climate spatial patterns and heterogeneity of hydrological patterns across the conterminous United States without downloading large climate datasets.
Kurihana, Takuya↗
Cloud Feedback Uncertainty in the Equatorial Pacific Across CMIP6 Models
Cloud feedback is the largest uncertainty in estimating Equilibrium Climate Sensitivity. In this study we focus on the equatorial Pacific, where CMIP6 model cloud feedback spread is notably large. Cloud radiative effects in this region are relevant for the global climate. Our findings show that models predict a consistent shift towards the ascent regime in response to El Nino-like sea surface warming. Models diverge in terms of the radiative impact due to differences in cloud characteristics in ascent and subsidence regimes. Using the observed relationship between circulation regime and cloud radiative effect, we find a reduction in the regional mean cloud feedback estimate from 0.77 to 0.22 W m -2 K -1 , though this does not substantially lessen the model spread in total feedback. Pathways to reduce this spread include: improving confidence in the regional ocean warming pattern, and using observations and models to understand cloud type and circulation interactions.
CMIP6↗
Sensitivity of Regional Climate to Deforestation in the Amazon Basin
The deforestation results in several adverse effect on the natural environment. The focus of this paper is on the effects of deforestation on land-surface processes and regional climate of the Amazon basin. In general, the effect of deforestation on climate are likely to depend on the scale of the defrosted area. In this study, we are interested in the effects due to deforestation of areas with a scale of about 250 km. Hence, a meso-scale climate model is used in performing numerical experiments on the sensitivity of regional climate to deforestation of areas with that size. It is found that deforestation results in less net surface radiation, less evaporation, less rainfall, and warmer surface temperature. The magnitude of the of the change in temperature is of the order 0.5 C, the magnitudes of the changes in the other variables are of the order of IO%. In order to verify some of he results of the numerical experiments, the model simulations of net surface radiation are compared to recent observations of net radiation over cleared and undisturbed forest in the Amazon. The results of the model and the observations agree in the following conclusion: the difference in net surface radiation between cleared and undisturbed forest is, almost, equally partioned between net solar radiation and net long-wave radiation. This finding contributes to our understanding of the basic physics in the deforestation problem.
Eltahir, Elfatih A. B.↗