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NASA NTRS2021

Land-Atmosphere Coupling at the U.S. Southern Great Plains: A Comparison on Local Convective Regimes Between ARM Observations, Reanalysis, and Climate Model Simulations

Using the 9-yr warm-season observations at the Atmospheric Radiation Measurement Southern Great Plains site, we assess the land-atmosphere (L-A) coupling in North American Regional Reanalysis (NARR) and two climate models: hindcasts with the Community Atmosphere Model version 5.1 by Cloud-Associated Parameterizations Testbed (CAM5-CAPT) and nudged runs with the Energy Exascale Earth System Model Atmosphere Model version 1 Regionally Refined Model (EAMv1-RRM). We focus on three local convective regimes and diagnose model behaviors using the Local Coupling metrics (Santanello et al. 2018). NARR agrees well with observations except a slightly warmer and drier surface with higher downwelling shortwave radiation and lower evaporative fraction. On clear-sky days, it shows warmer and drier early-morning conditions in both models with significant underestimates in surface evaporation by EAMv1-RRM. On the majority of the ARM-observed shallow cumulus days, there is no or little low-level clouds in either model. When captured in models, the simulated shallow cumulus shows much less cloud fraction and lower cloud bases than observed. On the days with late-afternoon deep convection, models tend to present a stable early-morning lower atmosphere more frequently than the observations, suggesting that the deep convection is triggered more often by elevated instabilities. Generally, CAM5-CAPT can reproduce the local L-A coupling processes to some extent due to the constrained early-morning conditions and large-scale winds. EAMv1-RRM exhibits large precipitation deficits and warm and dry biases towards mid-to-late summers, which may be an amplification through a positive L-A feedback among initial atmosphere and land states, convection triggering and large-scale circulations.

land-atmosphere↗

NASA NTRS2002

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/ South China Sea (SCS)/China, N. America and S. America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-C loud Exchange (PLACE) land surface model. PLACE allows for the effects of vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1997 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

Tao, W.-K.↗

NASA NTRS2014

Temperature and Humidity Profiles in the TqJoint Data Group of AIRS Version 6 Product for the Climate Model Evaluation

The Atmospheric Infrared Sounder (AIRS) mission is entering its 13th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing long-wave radiation, cloud properties, and trace gases. Thus AIRS data have been widely used, among other things, for short-term climate research and observational component for model evaluation. One instance is the fifth phase of the Coupled Model Intercomparison Project (CMIP5) which uses AIRS version 5 data in the climate model evaluation. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for data from the AIRS mission. The GES DISC, in collaboration with the AIRS Project, released data from the version 6 algorithm in early 2013. The new algorithm represents a significant improvement over previous versions in terms of greater stability, yield, and quality of products. The ongoing Earth System Grid for next generation climate model research project, a collaborative effort of GES DISC and NASA JPL, will bring temperature and humidity profiles from AIRS version 6. The AIRS version 6 product adds a new "TqJoint" data group, which contains data for a common set of observations across water vapor and temperature at all atmospheric levels and is suitable for climate process studies. How different may the monthly temperature and humidity profiles in "TqJoint" group be from the "Standard" group where temperature and water vapor are not always valid at the same time? This study aims to answer the question by comprehensively comparing the temperature and humidity profiles from the "TqJoint" group and the "Standard" group. The comparison includes mean differences at different levels globally and over land and ocean. We are also working on examining the sampling differences between the "TqJoint" and "Standard" group using MERRA data.

climate model evaluation↗

DOE OSTI2021

Land–Atmosphere Coupling at the U.S. Southern Great Plains: A Comparison on Local Convective Regimes between ARM Observations, Reanalysis, and Climate Model Simulations

Using the 9-yr warm-season observations at the Atmospheric Radiation Measurement Southern Great Plains site, in this work we assess the land–atmosphere (LA) coupling in the North American Regional Reanalysis (NARR) and two climate models: hindcasts with the Community Atmosphere Model version 5.1 by Cloud-Associated Parameterizations Testbed (CAM5-CAPT) and nudged runs with the Energy Exascale Earth System Model Atmosphere Model version 1 Regionally Refined Model (EAMv1-RRM). We focus on three local convective regimes and diagnose model behaviors using the local coupling metrics. NARR agrees well with observations except a slightly warmer and drier surface with higher downwelling shortwave radiation and lower evaporative fraction. On clear-sky days, it shows warmer and drier early-morning conditions in both models with significant underestimates in surface evaporation by EAMv1-RRM. On the majority of the ARM-observed shallow cumulus days, there is no or little low-level clouds in either model. When captured in models, the simulated shallow cumulus shows much less cloud fraction and lower cloud bases than observed. On the days with late-afternoon deep convection, models tend to present a stable early-morning lower atmosphere more frequently than the observations, suggesting that the deep convection is triggered more often by elevated instabilities. Generally, CAM5-CAPT can reproduce the local LA coupling processes to some extent due to the constrained early-morning conditions and large-scale winds. EAMv1-RRM exhibits large precipitation deficits and warm and dry biases toward mid-to-late summers, which may be an amplification through a positive LA feedback among initial atmosphere and land states, convection triggering and large-scale circulations.

58 GEOSCIENCES↗

NASA NTRS2019

Examining Seasonal Trends of the Martian Polar Warming with the NASA Ames Mars Global Climate Model

The presented work focuses on polar warming as a diagnostic of the mean circulation to increase our understanding of processes that control the mean meridional circulation and transport in the Mars’ middle atmosphere. The NASA Ames Mars Global Climate Model is utilized to isolate physical processes to determine their impact on polar warming and its seasonal trends.

Brecht, Amanda S.↗

NASA NTRS1989

Study of the atmospheric general circulation as an initial value problem with the NCAR Community Climate Model

The essential elements of the transition of a model atmosphere to the equilibrium state from two extreme rest states, a cold (240 K) state and a warm (310 K) state, were examined using the NCAR Community Climate Model. It is shown that the same equilibrium state was reached in the two spinup conditions, which was also the same that was reported for this model by Williamson and Williamson (1984), who started from still a different initial condition. The spinup from the cold initial condition was faster than that from the warm condition, although the final stages of the approach to equilibrium were very simular in both cases. It was also found that the spinup of the barotropic flow lagged behind that of the baroclinic flow and the thermal field, and the model tropics spinup was faster than that of the mid-latitudes.

Chen, Tsing-Chang↗

DOE OSTI2023

Connecting Large‐Scale Meteorological Patterns to Extratropical Cyclones in CMIP6 Climate Models Using Self‐Organizing Maps

Abstract Extratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2023

A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR

The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. Using the results obtained in the case of the SMB, surface and air temperature are assessed through the comparison of the modeled outputs with in situ and satellite measurement. The downscaled products show a considerable improvement in the case of the downscaled product with respect to the original coarse output, with the coefficient of determination (R 2 ) increasing from 0.868 for the original MAR output to 0.935 for the SMB downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the slope and from the value −235 mm w.e. yr -1 (original) to −57 mm w.e. yr -1 (downscaled) in the case of the intercept, considerably improving upon results previously published in the literature.

Greenland Ice Sheet↗

NASA NTRS1978

Climate modeling

The requirements for radiation measurements suitable for the understanding, improvement, and verification of models used in performing climate research are considered. Both zonal energy balance models and three dimensional general circulation models are considered, and certain problems are identified as common to all models. Areas of emphasis include regional energy balance observations, spectral band observations, cloud-radiation interaction, and the radiative properties of the earth's surface.

Source record↗

NASA NTRS1980

Comments on 'Some realistic modifications of simple climate models'

Lindzen and Farrell (LF) in 1977 argued that the eddy diffusion is not a good parameterization of meridional heat flux in tropical latitudes and that model sensitivity could be altered drastically if a more 'realistic' (nondiffusive) parameterization of tropical transports were included. LF suggested modifications to the heat transport term in Budyko's (1969) zonal energy-balance climate model. The authors do not believe that the modifications suggested by LF are necessarily more realistic than the original formulation, and thus it is not believed that the quantitative results offered by LF can be demonstrated as more realistic than those they replace. Reasons for the belief are discussed.

Warren, S. G.↗

NASA NTRS2013

How Well Do Global Climate Models Simulate the Variability of Atlantic Tropical Cyclones Associated with ENSO?

The variability of Atlantic tropical cyclones (TCs) associated with El Nino-Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. CLIVAR Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multi-model ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions in the TC activities during eastern Pacific (EP) and central Pacific (CP) El Nino events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Nino and stronger activity during La Nina. For CP El Nino, there is a slight increase in the number of TCs as compared with EP El Nino. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region as in observations. The difference between the models and observations is likely due to the bias of vertical wind shear in response to the shift of tropical heating associated with CP El Nino, as well as the model bias in the mean circulation.

Tropical Cyclones↗

NASA NTRS2008

Impacts of the IBM Cell Processor to Support Climate Models

NASA is interested in the performance and cost benefits for adapting its applications to the IBM Cell processor. However, its 256KB local memory per SPE and the new communication mechanism, make it very challenging to port an application. We selected the solar radiation component of the NASA GEOS-5 climate model, which: (1) is representative of column physics (approximately 50% computational time), (2) has a high computational load relative to transferring data from and to main memory, (3) performs independent calculations across multiple columns. We converted the baseline code (single-precision, Fortran) to C and ported it with manually SIMDizing 4 independent columns and found that a Cell with 8 SPEs can process 2274 columns per second. Compared with the baseline results, the Cell is approximately 5.2X, approximately 8.2X, approximately 15.1X faster than a core on Intel Woodcrest, Dempsey, and Itanium2, respectively. We believe this dramatic performance improvement makes a hybrid cluster with Cell and traditional nodes competitive.

Zhou, Shujia↗

NASA NTRS1992

Climate model calculations of the effects of volcanoes on global climate

An examination of the Northern Hemisphere winter surface temperature patterns after the 12 largest volcanic eruptions from 1883-1992 shows warming over Eurasia and North America and cooling over the Middle East which are significant at the 95 percent level. This pattern is found in the first winter after tropical eruptions, in the first or second winter after midlatitude eruptions, and in the second winter after high latitude eruptions. The effects are independent of the hemisphere of the volcanoes. An enhanced zonal wind driven by heating of the tropical stratosphere by the volcanic aerosols is responsible for the regions of warming, while the cooling is caused by blocking of incoming sunlight.

Robock, Alan↗

DOE OSTI2021

Global Temperature Responses to Large Tropical Volcanic Eruptions in Paleo Data Assimilation Products and Climate Model Simulations Over the Last Millennium

Abstract Large volcanic eruptions are one of the dominant perturbations to global and regional atmospheric temperatures on timescales of years to decades. Discrepancies remain, however, in the estimated magnitude and persistence of the surface temperature cooling caused by volcanic eruptions, as characterized by paleoclimatic proxies and climate models. We investigate these discrepancies in the context of large tropical eruptions over the Last Millennium using two state‐of‐the‐art data assimilation products, the Paleo Hydrodynamics Data Assimilation product (PHYDA) and the Last Millennium Reanalysis (LMR), and simulations from the National Center for Atmospheric Research Community Earth System Model‐Last Millennium Ensemble (NCAR CESM‐LME). We find that PHYDA and LMR estimate mean global and hemispheric cooling that is similar in magnitude and persistence once effects from eruptions occurring in short succession are removed. The estimates also compare well to Northern‐Hemisphere reconstructions based solely or partially on tree‐ring density, which have been proposed as the most accurate proxy estimates of surface cooling due to volcanism. All proxy‐based estimates also agree well with the magnitude of the mean cooling simulated by the CESM‐LME. Differences remain, however, in the spatial patterns of the temperature responses in the PHYDA, LMR, and the CESM‐LME. The duration of cooling anomalies also persists for several years longer in the PHYDA and LMR relative to the CESM‐LME. Our results demonstrate progress in resolving discrepancies between proxy‐ and model‐based estimates of temperature responses to volcanism, but also indicate these estimates must be further reconciled to better characterize the risks of future volcanic eruptions.

Tejedor, E.↗

DOE OSTI2020

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term, high-frequency measurements from ARM in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2009

Overview of Proposal on High Resolution Climate Model Simulations of Recent Hurricane and Typhoon Activity: The Impact of SSTs and the Madden Julian Oscillation

This talk gives an update on the progress and further plans for a coordinated project to carry out and analyze high-resolution simulations of tropical storm activity with a number of state-of-the-art global climate models. Issues addressed include, the mechanisms by which SSTs control tropical storm. activity on inter-annual and longer time scales, the modulation of that activity by the Madden Julian Oscillation on sub-seasonal time scales, as well as the sensitivity of the results to model formulation. The project also encourages companion coarser resolution runs to help assess resolution dependence, and. the ability of the models to capture the large-scale and long-terra changes in the parameters important for hurricane development. Addressing the above science questions is critical to understanding the nature of the variability of the Asian-Australian monsoon and its regional impacts, and thus CLIVAR RAMP fully endorses the proposed tropical storm simulation activity. The project is open to all interested organizations and investigators, and the results from the runs will be shared among the participants, as well as made available to the broader scientific community for analysis.

Schubert, Siegfried↗

NASA NTRS2014

Near-Surface Meteorology During the Arctic Summer Cloud Ocean Study (ASCOS): Evaluation of Reanalyses and Global Climate Models.

Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.

surface energy↗

NASA NTRS2019

ESD Reviews: Model Dependence in Multi-Model Climate Ensembles: Weighting, Sub-Selection and Out-Of-Sample Testing

The rationale for using multi-model ensembles in climate change projections and impacts research is often based on the expectation that different models constitute independent estimates; therefore, a range of models allows a better characterisation of the uncertainties in the representation of the climate system than a single model. However, it is known that research groups share literature, ideas for representations of processes, parameterisations, evaluation data sets and even sections of model code. Thus, nominally different models might have similar biases because of similarities in the way they represent a subset of processes, or even be near-duplicates of others, weakening the assumption that they constitute independent estimates. If there are near-replicates of some models, then treating all models equally is likely to bias the inferences made using these ensembles. The challenge is to establish the degree to which this might be true for any given application. While this issue is recognised by many in the community, quantifying and accounting for model dependence in anything other than an ad-hoc way is challenging. Here we present a synthesis of the range of disparate attempts to define, quantify and address model dependence in multi-model climate ensembles in a common conceptual framework, and provide guidance on how users can test the efficacy of approaches that move beyond the equally weighted ensemble. In the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6), several new models that are closely related to existing models are anticipated, as well as large ensembles from some models. We argue that quantitatively accounting for dependence in addition to model performance, and thoroughly testing the effectiveness of the approach used will be key to a sound interpretation of the CMIP ensembles in future scientific studies.

Abramowitz, Gab↗