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At least 307 records · Page 17
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NASA NTRS2016

Evaluation of Current Planetary Boundary Layer Retrieval Capabilities from Space

The PBL over land remains a significant gap in our water and energy cycle understanding from space. This work combines unique NASA satellite and model products to demonstrate the ability of current sensors (advanced IR sounding and lidar) to retrieve PBL properties and in turn their potential to be used globally to evaluate and improve weather and climate prediction models. While incremental progress has been made in recent AIRS retrieval versions, insufficient vertical resolution remains in terms of detecting PBL properties. Lidar shows promise in terms of detecting vertical gradients (and PBLh) in the lower troposphere, but daytime conditions over land remain a challenge due to noise, and their coverage is limited to approximately 2 weeks or longer return times.

AIRS↗
NASA NTRS2017

How the Emitted Size Distribution and Mixing State of Feldspar Affect Ice Nucleating Particles in a Global Model

The effect of aerosol particles on ice nucleation and, in turn, the formation of ice and mixed phase clouds is recognized as one of the largest sources of uncertainty in climate prediction. We apply an improved dust mineral specific aerosol module in the NASA GISS Earth System ModelE, which takes into account soil aggregates and their fragmentation at emission as well as the emission of large particles. We calculate ice nucleating particle concentrations from K-feldspar abundance for an active site parameterization for a range of activation temperatures and external and internal mixing assumption. We find that the globally averaged INP concentration is reduced by a factor of two to three, compared to a simple assumption on the size distribution of emitted dust minerals. The decrease can amount to a factor of five in some geographical regions. The results vary little between external and internal mixing and different activation temperatures, except for the coldest temperatures. In the sectional size distribution, the size range 24 micrometer contributes the largest INP number.

Perlwitz, Jan P.↗
NASA NTRS2018

Investigating Extreme Events in the NASA GEOS Multiscale Modeling System

Advances in computing capabilities and scientific development have come together to evolve general circulation models into multi-scale Earth system modeling tools. The Goddard Earth Observing System (GEOS) model is one such example of this evolution. The GEOS model is driven by the finite-volume cubed-sphere (FV3) non-hydrostatic dynamical core. Surrounding FV3 is a scale-aware physics package and data assimilation capability permitting multi-scale application of GEOS for sub-seasonal to seasonal climate prediction, medium range weather prediction, and global mesoscale modeling at convection allowing resolutions. GEOS also includes a comprehensive chemistry package representing a range of capabilities from basic chemistry and interactve aerosols and gaseous species, to carbon emissions and uptake, and complex ozone photochemistry. In this study, we apply the GEOS model to study the fidelity of these processes with increasing horizontal resolution and scale-aware processes in GEOS on extreme events. The GEOS model is run for 40-days beginning in August 2016 at three uniform global resolutions of 13-km (c768), 6-km (c1536) and 3-km (c3072) with 72 vertical levels up to 0.01mb. The model physics use the Grell-Freitas scale-aware convection scheme to dynamically reduce the role of parameterized deep convection as resolved scale processes in the model take over at higher resolutions. We will include high-resolution global emissions and fluxes of aerosols and carbon downscaled from recent satellite observations. We will compare these simulations with reanalyses and observations, focusing on rainfall, clouds and radiative forcing at hourly to monthly timescales. We will closely examine the probability distribution of precipitation intensities and radiative properties of clouds on a daily time scale. In addition, we will focus on extreme events, in particular the diurnal cycle of convection over the US and the frequency and physical nature of organized convection and heavy rain events across the globe.

Putman, William↗
NASA NTRS2018

A Satellite-Based Estimate of Combustion Aerosol Cloud Microphysical Effects over the Arctic Ocean

Climate predictions for the rapidly changing Arctic are highly uncertain, largely due to a poor understanding of the processes driving cloud properties. In particular, cloud fraction (CF) and cloud phase (CP) have major impacts on energy budgets, but are poorly represented in most models, often because of uncertainties in aerosol–cloud interactions. Here, we use over 10 million satellite observations coupled with aerosol transport model simulations to quantify large scale microphysical effects of aerosols on CF and CP over the Arctic Ocean during polar night, when direct and semi-direct aerosol effects are minimal. Combustion aerosols over sea ice are associated with very large (~10W/sq.m) differences in longwave cloud radiative effects at the sea ice surface. However, co-varying meteorological changes on factors such as CF likely explain the majority of this signal. For example, combustion aerosols explain at most 40% of the CF differences between the full dataset and the clean-condition subset, compared to between 57% and 91% of the differences that can be predicted by co-varying meteorology. After normalizing for meteorological regime, aerosol microphysical effects have small but significant impacts on CF, CP, and precipitation frequency on an Arctic-wide scale. These effects indicate that dominant aerosol–cloud microphysical mechanisms are related to the relative fraction of liquid-containing clouds, with implications for a warming Arctic.

Zamora, Lauren M.↗
NASA NTRS2018

PACE Technical Report Series, Volume 4: Cloud Retrievals in the PACE Mission: PACE Science Team Consensus Document

Earth is a complex dynamical system exhibiting continuous change in its atmosphere, ocean,and surface elements. Nearly all (99.97%) of the energy driving these systems is linked to the Sun. Measurements of reflected sunlight contain a unique signature of wavelength-specific scattering and absorption interactions occurring between incoming solar energy and atmospheric (molecules, aerosols,clouds) and surface features Clouds can affect significantly both shortwave and long wave radiation, depending on altitude/vertical structure, thermodynamic phase, and optical properties. Low, warm, and optically thick clouds predominantly have a cooling effect, while high, cold, optically thin clouds can cause warming by absorbing warmer radiation emitted from the surface and lower atmosphere.When the net difference between outgoing and incoming solar radiation is matched by the net infrared radiation emitted to space, the Earth's climate is in radiative balance. While radiative forcing components (GHGs, aerosols - direct and indirect) contribute to a net radiative imbalance, climate sensitivity is ultimately determined by the contribution of various system feed backs. The role of cloud feedback in a warming climate is currently the largest inter-model uncertainty in climate sensitivity and therefore in climate prediction [Bony and Dufresne 2005]. A comprehensive understanding of current cloud propertiesand dynamic/microphysical processes requires a global perspective from satellites.

Plankton, Aerosol, Cloud, ocean Ecosystem (PACE)↗
NASA NTRS2019

Laboratory for Atmospheres Instrument Systems Report

Studies of the atmospheres of our solar system's planets including our own require a comprehensive set of observations, relying on instruments on spacecraft, aircraft, balloons, and on the surface. These instrument systems perform one or both of the following: 1) provide information leading to a basic understanding of the relationship between atmospheric systems and processes, and 2) serve as calibration references for satellite instrument validation. Laboratory personnel define requirements, conceive concepts, and develop instrument systems for spaceflight missions, and for balloon, aircraft, and ground-based observations. Balloon and airborne platforms facilitate regional measurements of precipitation, cloud systems, and ozone from high-altitude vantage points, but still within the atmosphere. Such platforms serve as stepping-stones in the development of space instruments. Satellites provide nearly global coverage of the Earth with spatial resolutions and repetition rates that vary from system to system. The products of atmospheric remote sensing are invaluable for research associated with water vapor, ozone, trace gases, aerosol particles, clouds, precipitation, and the radiative and dynamic processes that affect the climate of the Earth. These parameters also provide the basic information needed to develop models of global atmospheric processes and weather and climate prediction. Laboratory scientists also participate in the design of data processing algorithms, calibration techniques, and the data processing systems.

Platnick, Steven E.↗
NASA NTRS2019

The Role of Oceanic Processes in the Initiation of Boreal Winter Intraseasonal Oscillations over the Indian Ocean

Observational analyses and a hierarchy of ocean general circulation model (OGCM) experiments were performed to understand the influence of oceanic processes on the warm sea surface temperature anomalies (SSTAs) prior to the convection initiation of boreal winter intraseasonal oscillations (ISOs), including the Madden-Julian Oscillation (MJO), in the equatorial Indian Ocean. We found 39 strong ISOs that passed over the Indian Ocean Warm Pool region during the November-April season of the 2001-2012 period. 17/39 ISO events initiated in the Seychelles-Chagos Thermocline Ridge (SCTR) before propagating eastward; the remaining events initiated in the southern Arabian Sea (6) or Warm Pool (16) regions. The SCTR event set was notable in that it contained more global-scale MJOs (71-76%), as defined by the RMM and OMI indices, than the WP events (25-44%). Additionally, ~24% (44%) of the SCTR (Warm Pool) events were preceded by strong oceanic process-induced SSTAs of similar magnitude to those of shortwave radiative and turbulent heat fluxes. The Arabian Sea events, however, were not associated with statistically significant SSTA signals prior to convection. Based on a mixed layer heat budget analysis, entrainment and upwelling reduction were the dominant oceanic processes contributing to the warming, in contrast with boreal summer, when horizontal advection dominated. We examined several case studies, including primary MJO events, where oceanic Rossby waves were associated with the entrainment and upwelling reduction. Two simple atmospheric boundary layer convergence models revealed that the SSTAs contributed at least half of the total convergence and suggested that the ocean dynamical effect was responsible for the majority of SSTA-forced convergence for those case studies. These results underscore the need for climate prediction models to accurately represent the ocean structure and processes to include the effects of oceanic predictors.

West, B. Jason↗
NASA NTRS2020

Impact of Gauge-Based Precipitation Corrections on the Skill of SMAP Level-4 Soil Moisture Estimates

The NASA Soil Moisture Active Passive (SMAP) mission provides observations of L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations at a resolution of ~40 km globally every 2-3 days. These observations are routinely assimilated into the NASA Catchment land surface model to generate the Level-4 Soil Moisture (L4_SM) product, which provides global estimates of surface and root-zone soil moisture, soil temperature, and surface fluxes (among others) at 9-km, 3-hourly resolution with ~2.5-day latency. The Catchment land surface model in the L4_SM algorithm is driven with 0.25°, hourly surface meteorological forcing data from the NASA Goddard Earth Observing System (GEOS) "forward-processing" product. Outside of Africa and the high latitudes, the GEOS precipitation forcing is corrected using the Climate Prediction Center Unified (CPCU) gauge-based, 0.5°, daily precipitation product.Soil moisture estimates from the L4_SM product were previously shown to improve over land model-only estimates that do not benefit from the assimilation of Tb observations, thereby demonstrating the value of assimilating SMAP observations for soil moisture estimation. In this presentation, we further isolate the contribution of the gauge-based precipitation corrections to the skill of the L4_SM soil moisture estimates. Specifically, we compare the skill of the L4_SM soil moisture to that of separate model-only and assimilation estimates obtained without the benefit of the gauge-based precipitation corrections.Preliminary results suggest that the soil moisture skill added by the CPCU-based precipitation corrections primarily depends on the quality of the CPCU precipitation product and is greatest in regions where the CPCU gauge network is dense and reliable. Conversely, in regions where the CPCU product is known to be of poor quality, for example in central Australia, the assimilation of SMAP Tb observations provides the most benefit. The presentation will provide an in-depth evaluation of the soil moisture skill of the model-only and assimilation estimates vs. independent in situ and satellite measurements.

Reichle, Rolf↗
NASA NTRS2020

Creating and Using Sensors That Tell Us About Precipitation

Precipitation is deceptively simple to measure - just put a container in the back yard - and this was the only technology available until radar was discovered to be capable of sensing precipitation in the 1940's,leading to quantitative estimates by the 1970's.Meanwhile, satellite-based sensors started advancing.The first precipitation estimates from space re purposed the existing geosynchronous satellite infrared (GEO-IR) data, but purpose-built passive microwave (PMW) sensors soon became a reality. In 1987, the launch of the first Special Sensor Microwave/Imager on the Defense Meteorological Satellite Program F08 by the U.S. Department of Defense, and their decision to open the dataset top public use, created a boom in precipitation algorithms that continues to this day. Experimental work to create a global multi-satellite product by Global Precipitation Climatology Project, and then a "virtual constellation"of PMW sensors from satellite agencies around the globe by the NASA/JAXA Tropical Rainfall Measuring Mission (TRMM) and by NOAA/NWS Climate Prediction Center, resulted in a new generation of quasi-global multi-satellite precipitation estimates at increasingly fine time and space scales. TRMM and the NASA/JAXA Global Precipitation Measurement mission have hosted precipitation radars in space, providing critical new quasi-global information about 3-D precipitation structures and enabling improved calibration of the PMW constellation's estimates.

Huffman, George J.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-31549-DND

Aerosols (mostly) scatter sunlight back to space, partially compensating for CO2 warming. To match the 20th century temperature record, models with low climate sensitivity require a relatively higher total anthropogenic forcing. Observational constraints on aerosol radiative effects will help to improve climate predictions.

Dave Winker↗
NASA NTRSDate not supplied

A Framework for Evaluating Climate Model Performance Metrics

The CMIP5 archive contains future climate projections from over 50 models provided by dozens of modeling centers from around the world. Individual model projections, however, are subject to biases created by structural model uncertainties. As a result, ensemble averaging of multiple models is often used to add value to model projections: consensus projections have been shown to consistently outperform individual models. Previous reports for the IPCC establish climate change projections based on an equal-weighted average of all model projections. However, certain models reproduce climate processes better than other models. Should models be weighted based on performance? Unequal ensemble averages have previously been constructed using a variety of mean state metrics. What metrics are most relevant for constraining future climate projections? This project develops a framework for systematically testing metrics in models to identify optimal metrics for unequal weighting multi-model ensembles. A unique aspect of this project is the construction and testing of climate process-based model evaluation metrics. A climate process-based metric is defined as a metric based on the relationship between two physically related climate variables?e.g., outgoing longwave radiation and surface temperature. Metrics are constructed using high-quality Earth radiation budget data from NASA's Clouds and Earth's Radiant Energy System (CERES) instrument and surface temperature data sets. It is found that regional values of tested quantities can vary significantly when comparing weighted and unweighted model ensembles. For example, one tested metric weights the ensemble by how well models reproduce the time-series probability distribution of the cloud forcing component of reflected shortwave radiation. The weighted ensemble for this metric indicates lower simulated precipitation (up to .7 mm/day) in tropical regions than the unweighted ensemble: since CMIP5 models have been shown to overproduce precipitation, this result could indicate that the metric is effective in identifying models which simulate more realistic precipitation. Ultimately, the goal of the framework is to identify performance metrics for advising better methods for ensemble averaging models and create better climate predictions.

Noel C Baker↗
NASA NTRS2020

TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI): motivations and protocol version 1.0

Upcoming telescopes such as the James Webb Space Telescope (JWST), the European Extremely Large Telescope (E-ELT), the Thirty Meter Telescope (TMT) or the Giant Magellan Telescope (GMT) may soon be able to characterize, through transmission, emission or reflection spectroscopy, the atmospheres of rocky exoplanets orbiting nearby M dwarfs. One of the most promising candidates is the late M-dwarf system TRAPPIST-1, which has seven known transiting planets for which transit timing variation (TTV) measurements suggest that they are terrestrial in nature, with a possible enrichment in volatiles. Among these seven planets, TRAPPIST-1e seems to be the most promising candidate to have habitable surface conditions, receiving ∼66 % of the Earth's incident radiation and thus needing only modest greenhouse gas inventories to raise surface temperatures to allow surface liquid water to exist. TRAPPIST-1e is, therefore, one of the prime targets for the JWST atmospheric characterization. In this context, the modeling of its potential atmosphere is an essential step prior to observation. Global climate models (GCMs) offer the most detailed way to simulate planetary atmospheres. However, intrinsic differences exist between GCMs which can lead to different climate prediction and thus observability of gas and/or cloud features in transmission and thermal emission spectra. Such differences should preferably be known prior to observations. In this paper we present a protocol to intercompare planetary GCMs. Four testing cases are considered for TRAPPIST-1e, but the methodology is applicable to other rocky exoplanets in the habitable zone. The four test cases included two land planets composed of modern-Earth and pure-CO2 atmospheres and two aqua planets with the same atmospheric compositions. Currently, there are four participating models (LMDG, ROCKE-3D, ExoCAM, UM); however, this protocol is intended to let other teams participate as well.

Thomas Jean Daniel Fauchez↗
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↗
NASA NTRSDate not supplied

Comparison of INP Parameterizations for Dust Minerals in Climatological Simulations With a Global Model

The effect of aerosol particles on ice nucleation and, in turn, the formation of ice and mixed phase clouds is recognized as one of the largest sources of uncertainty in weather and climate prediction. We utilize an improved sectional dust module in NASA GISS Earth System ModelE2.1, which distinguishes eight different mineral species and accretions between iron oxides and the other minerals. Simulations over a period of 20 years have been carried out with this model, and the mineral fields and other model variables (temperature, relative humidity) are used to calculate the ice nucleating particle (INP) number concentration, applying time-independent and time-dependent INP parameterizations, such as active site parameterization and water activity based immersion freezing model (ABIFM). We study how the dependence of the parameterizations on different model variables affects the mean INP number concentration. The sensitivity of the INP number concentration to fundamental dust properties such as emitted mineral size distributions and mixing state between minerals is also investigated. Results show that the sensitivity of the total INP number concentration to the emitted dust size distribution is rather small, but the sensitivity over the whole size range obscures offsetting differences in the magnitude and the sign of the sensitivity between smaller and larger particles.

INP Parameterizations↗
NASA NTRS2021

The Contributions of Gauge-Based Precipitation and SMAP Brightness Temperature Observations to the Skill of the SMAP Level-4 Soil Moisture Product

Soil Moisture Active Passive (SMAP) mission L-band brightness temperature (Tb) observations are routinely assimilated into the Catchment land surface model to generate Level-4 Soil Moisture (L4_SM) estimates of global surface and root-zone soil moisture at 9-km, 3-hourly resolution with ~2.5-day latency. The Catchment model in the L4_SM algorithm is driven with ¼-degree, hourly surface meteorological forcing data from the Goddard Earth Observing System (GEOS). Outside of Africa and the high latitudes, GEOS precipitation is corrected using Climate Prediction Center Unified (CPCU) gauge-based, ½-degree, daily precipitation. L4_SM soil moisture was previously shown to improve over land model-only estimates that use CPCU precipitation but no Tb assimilation (CPCU_SIM). Here, we additionally examine the skill of model-only (CTRL) and Tb assimilation-only (SMAP_DA) estimates derived without CPCU precipitation. Soil moisture is assessed versus in situ measurements in well-instrumented regions and globally through the Instrumental Variable (IV) method using independent soil moisture retrievals from the Advanced Scatterometer. At the in situ locations, SMAP_DA and CPCU_SIM have comparable soil moisture skill improvements relative to CTRL for the unbiased root-mean-square error (surface and root-zone) and correlation metrics (root-zone only). In the global average, SMAP Tb assimilation increases the surface soil moisture anomaly correlation by 0.10-0.11 compared to an increase of 0.02-0.03 from the CPCU-based precipitation corrections. The contrast is particularly strong in central Australia, where CPCU is known to have errors and observation-minus-forecast Tb residuals are larger when CPCU precipitation is used. Validation versus streamflow measurements in the contiguous U.S. reveals that CPCU precipitation provides most of the skill gained in L4_SM runoff estimates over CTRL.

SMAP↗
NASA NTRS2013

Soil Moisture Active Passive (SMAP) observer power system architecture

The Soil Moisture Active and Passive (SMAP) observer is scheduled for launch in 2014. The primary science objective of SMAP is the high-resolution mapping of earth’s soil moisture. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The SMAP orbit, sun-synchronous with an altitude of 680 km, was chosen to optimize the sampling characteristics of the instruments while ensuring that the resolution requirements are met. The combined active radar and passive radiometer measurement approach takes advantage of the spatial resolutions of the radar (3 km x 1000 km) and the radiometer (39 km x 47 km).

Carr, Gregory↗
NASA NTRS2021

Confronting Future Models with Future Satellite Observations of Clouds and Aerosols

The NASA Aerosol, Clouds, Convection and Precipitation (ACCP) Study convened a workshop in November 2020 to understand the future of modeling aerosols, clouds, convection and precipitation, and how satellite data can contribute to that future. ACCP is a project to define a satellite mission to be launched late in the 2020’s to advance cloud and aerosol science, following the recommendations of the latest NASA Decadal Survey. The ACCP modeling workshop goal was to answer the following questions: 1. What will be the critical science questions for clouds and aerosols in 10 years? 2. Where will simulations of clouds and aerosols across scales of space (process models to global) and time (nowcasting to climate prediction) be in 10 years? 3. What data will be available from space? What data would provide the most benefit? 4. What are the state of the art methods for confronting models with cloud and aerosol observations, including assimilation and climatological analysis techniques? The virtual workshop was anchored by a series of pre-recorded talks. Two days of synchronous sessions focused on discussion of the talks, along with small group breakout exercises. After an introduction to the ACCP concept came a panel discussing the future of modeling clouds and aerosols across scales. Participants were then asked to contribute their ideas. On the second day, there were two panel discussions. First came a discussion of the future of satellite observing systems. Second was a discussion of model-data synthesis methods. Finally, participants were asked to develop their own model-data synthesis proposal. The meeting began with an overview of the ACCP mission concept by Graeme Stephens (NASA-JPL). ACCP is a satellite mission for clouds and aerosols, likely anchored by advanced active lidar and radar systems in space, designed to observe detailed aerosol profile and type information, as well as cloud microphysics and dynamics. ACCP will integrate across sensors and observational types to get multi-spectral views of the same scenes, with better resolution than is available today. Launch is scheduled for 2027 or 2029. ACCP is being thought of as a comprehensive mission that may comprise more than one platform and more than one orbit plane (i.e., inclined and polar), with multiple combinations of sensors.

Future Models↗
NASA NTRSDate not supplied

Survey of microphysical properties of marine boundary-layer clouds in the Western North Atlantic

Oceanic low level clouds strongly affect the atmospheric radiation budget. Uncertainties in their microphysical properties and cover currently limit the accuracy of climate predictions. Further, studies quantifying the relative importance of aerosol and dynamics on cloud properties in specific meteorological regimes are poorly constrained by observations in the Western North Atlantic boundary layer. Low level clouds were measured during the Aerosol Cloud meTereology Interactions oVer the western ATlantic Experiment (ACTIVATE) campaign in winter and summer 2020. The two NASA LaRC research aircraft HU-25 Falcon and UC-12 B-200 King Air conducted 35 simultaneous flights to investigate aerosol-cloud interactions of maritime clouds and their impact on radiation. Number concentration, liquid water content, ice water content, and particle size distribution in the size range of 3 µm to 1460 µm in diameter were measured with the fast forward scattering cloud probe (FCDP) and 2-dimensional optical array imaging probe (2D-S) onboard the Falcon. Here, we present an overview of late winter (February-March) and late summer (August-September) oceanic cloud properties in the region 65°W to 80°W and 30°N to 40°N. We compare cloud properties in these two seasons and investigate their dependence on meteorological parameters and aerosol abundance. In a case study, we present cloud observations in a cold air outbreak event on 1 March 2020 with a specific focus on mixed-phase clouds.

microphysical properties↗