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NASA NTRS1992

Atmospheric water vapor measurements - Comparison of microwave radiometry and lidar

The NASA/GSFC Crustal Dynamics Project microwave water vapor radiometer (J03) is evaluated in terms of measurements of the integrated precipitable water vapor content of a particular column of the troposphere. The measurements were taken during the Atmospheric Moisture Intercomparison Study (ATMIS) held at Wallops Island (Virginia) during April 1989. Water vapor sensing instruments used during ATMIS, included radiometers, radiosondes, and the NASA/GSFC Raman lidar. Comparisons between water vapor measurements by the radiometer and the lidar yielded a correlation coefficient of 0.998 and rms differences for three nights of -0.2 +/- 0.2 mm (April 11-12), -0.8 +/- 0.5 mm (April 16-17), and -0.4 +/- 0.3 mm (April 17-18). The integrated precipitable water vapor measurements for these three nights were approximately 5, 10 and 21 mm, respectively. This study shows that the radiometer provides accurate continuous measurements of the water vapor integrated through the depth of the atmosphere.

England, Martin N.↗

NASA NTRS1998

Multi-Satellite Estimates of Land-Surface Properties for Determination of Energy and Water Budgets

Using the WETNET database, existing methods for the estimation of surface wetness from SSM/I data have been assessed and further developed. A physical-statistical method for optimal estimation of daily surface heat flux and Bowen ratio on the mesoscale has been developed and tested. This method is based on observations of daytime planetary boundary layer (PBL) growth from operational ravansonde and daytime land-surface temperature amplitude from Geostationary Operational Environmental (GOES) satellites. The mesoscale patterns of these heat fluxes have been compared with an AVHRR-based vegetation index and surface wetness (separately estimated from SSM/I and in situ observations). Cases of the 1988 Midwest drought and a surface/atmosphere moisture gradient (dry-line) in the southern Plains were studied. The analyses revealed significant variations in sensible heat flux (S(sub 0), and Bowen ratio, B(sub 0)) associated with vegetation cover and antecedent precipitation. Relationships for surface heat flux (and Bowen ratio) from antecedent precipitation and vegetation index have been developed and compared to other findings. Results from this project are reported in the following reviewed literature.

Menzel, W. Paul↗

NASA NTRS1997

Consistency Between Divergent Circulations from Reanalysis Data Sets and Satellite-Derived Precipitation, Radiation, and Surface Fluxes

Large-scale divergent circulations are part of the atmospheric dynamic response to diabatic heating from condensation, radiative processes, and surface heat fluxes. Vertical motion and the associated divergent wind is thus intimately tied to the hydrologic cycle and the global heat balance. Despite its importance, the divergent circulation is too small in comparison to the rotational flow to measure directly with any accuracy. Vertical motions are recovered diagnostically from reanalyses and, as such, are subject to shortcomings in model physics, numerics, and data availability. We use several GEWEX pre-EOS data sets derived from satellite data to assess interannual divergent flow anomalies in the NCEP, GSFC, and GSFC DAO analyse. Among the data sets are monthly, 2.5 degree gridded precipitation (MSU and SSM/I-based), TOA radiative fluxes from ERBS, surface radiative fluxes from the SRB project, and surface latent and sensible flux estimates from SSM/I. Most of these data sets can be considered as independent of the reanalysis fields. We focus largely on the period 1987-1989 encompassing a strong El Nino / la Nina couplet. Consequently we emphasize interannual changes rather than climatological aspects of the reanalyses. In the processes of this study we use simple integral constraints enforced through the satellite-derived data sets to derive corrections to the divergent circulation produced from the reanalyses. We examine the implications of these corrections in describing how perturbations to the tropical heat balance evolve during a warm / cool couplet. In particular the perturbations to the planetary scale water vapor transport, and the resulting changes in TOA and surface radiative fluxes are considered.

Robertson, Franklin R.↗

NASA NTRS2010

The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.

Koster, Randal↗

NASA NTRS2016

North American Megadroughts in the Common Era: Reconstructions and Simulations

During the Medieval Climate Anomaly (MCA), Western North America experienced episodes of intense aridity that persisted for multiple decades or longer. These megadroughts are well documented in many proxy records, but the causal mechanisms are poorly understood. General circulation models (GCMs) simulate megadroughts, but do not reproduce the temporal clustering of events during the MCA, suggesting they are not caused by the time history of volcanic or solar forcing. Instead, GCMs generate megadroughts through (1) internal atmospheric variability, (2) sea-surface temperatures, and (3) land surface and dust aerosol feedbacks. While no hypothesis has been definitively rejected, and no GCM has accurately reproduced all features (e.g., timing, duration, and extent) of any specific megadrought, their persistence suggests a role for processes that impart memory to the climate system (land surface and ocean dynamics). Over the 21st century, GCMs project an increase in the risk of megadrought occurrence through greenhouse gas forced reductions in precipitation and increases in evaporative demand. This drying is robust across models and multiple drought indicators, but major uncertainties still need to be resolved. These include the potential moderation of vegetation evaporative losses at higher atmospheric [CO2], variations in land surface model complexity, and decadal to multidecadal modes of natural climate variability that could delay or advance onset of aridification over the the next several decades. Because future droughts will arise from both natural variability and greenhouse gas forced trends in hydroclimate, improving our understanding of the natural drivers of persistent multidecadal megadroughts should be a major research priority.

atmospheric temperature↗

NASA NTRS2016

Impacts of Extreme Events on Human Health

Increased Exposure to Extreme Events Key Finding 1: Health impacts associated with climate-related changes in exposure to extreme events include death, injury, or illness; exacerbation of underlying medical conditions; and adverse effects on mental health[High Confidence]. Climate change will increase exposure risk in some regions of the United States due to projected increases in the frequency and/or intensity of drought, wildfires, and flooding related to extreme precipitation and hurricanes [Medium Confidence].Disruption of Essential Infrastructure Key Finding 2: Many types of extreme events related to climate change cause disruption of infrastructure, including power, water, transportation, and communication systems, that are essential to maintaining access to health care and emergency response services and safeguarding human health [High Confidence].Vulnerability to Coastal Flooding Key Finding 3: Coastal populations with greater vulnerability to health impacts from coastal flooding include persons with disabilities or other access and functional needs, certain populations of color, older adults, pregnant women and children, low-income populations, and some occupational groups [High Confidence].Climate change will increase exposure risk to coastal flooding due to increases in extreme precipitation and in hurricane intensity and rainfall rates, as well as sea level rise and the resulting increases in storm surge.

floods↗

NASA NTRS2023

Changing Characteristics of Tropical Extreme Precipitation-Cloud Regimes in Warmer Climates

In this paper, we have investigated the changing characteristics of climatic scale (monthly) tropical extreme precipitation in warming climates using the Energy Exascale Earth System Model (E3SM). Results are from Atmospheric Model Intercomparison Project (AMIP)-type simulations driven by a) control experiment with present-day sea surface temperature (SST) and CO 2 concentration, b) P4K, same as in a) but with uniform increase by 4K in SST globally, and c) same as in a), but with imposed SST and CO 2 concentration from outputs of coupled E3SM forced by 4xCO 2 concentration. We find that as the surface warms under P4K and 4xCO 2 , both convective and stratiform rain increase. Importantly, there is increasing fractional contribution of stratiform rain as a function of precipitation intensity, with the most extreme but rare events occurring preferentially over land more than ocean, more so under 4xCO 2 than P4K. Extreme precipitation is facilitated by increased precipitation efficiency, reflecting accelerated rates of recycling of precipitation-cloud water (both liquid and ice phases) in regions with colder anvil cloud tops. Changes in vertical profiles of clouds, condensation heating and vertical motions indicate increasing precipitation-cloud-circulation organization from control, P4K to 4xCO 2 . Results suggest that large-scale ocean warming, i.e., P4K, is the primary cause contributing to organization structure resembling the well-known Mesoscale Convective System (MCS) for increased extreme precipitation on shorter (hourly to daily) time scales. Additional 4xCO 2 atmospheric radiative heating, and dynamically consistent anomalous SST further amplifies the MCS organization under P4K. Analyses of the surface moist static energy distribution show that increase in surface moisture (temperature) under P4K and 4xCO 2 is the key driver leading to enhanced convective instability over tropical ocean (land). However, the fast and large increase in land surface temperature and lack of available local moisture result in strong reduction in land surface relative humidity, reflecting severe drying and enhanced convective inhibition (CIN). It is argued that very extreme and rare “record-breaking” precipitation events found over land under P4K, more so under 4xCO 2 , are likely due to the delayed onset of deep convection, i.e., the longer the suppression of deep convection by CIN, the more severe the extreme precipitation when eventually occur, due to the release of large amount of stored surplus convective available potential energy in the lower troposphere during prolonged CIN.

climate-scale extreme tropical precipitation↗

DOE OSTI2026

Soil Moisture Buffers the Impact of Precipitation Variability on Ecosystem Productivity

Water availability governs ecosystem productivity, yet estimates of vegetation sensitivity to water can differ greatly depending on whether the sensitivity is examined spatially or temporally. In particular, the spatial sensitivity is often reported to be much stronger than temporal sensitivities, leading to highly uncertain projections of ecosystem responses to future climate change when using space-for-time substitution. The large difference between spatial and temporal sensitivities remains unexplained. Prior research, however, primarily relied on precipitation as the water availability proxy, whereas vegetation responds to soil moisture. Here, we combined satellite estimates of vegetation productivity with soil moisture data across water-limited ecosystems of the continental United States (CONUS) to identify a convergent sensitivity of productivity to water availability. Using precipitation, we show that temporal sensitivity is 66% lower than spatial sensitivity overall. Our analysis identified the cause of the difference to be primarily driven by the seasonal variability of water availability, rooting depth, and soil properties. When using soil moisture instead of precipitation, we observed widespread convergence in the spatial and temporal sensitivities—that is, the two sensitivities became much more similar in magnitude across all water-limited ecosystems within CONUS. These results show that overlooking soil hydrology can inflate perceived discrepancies between spatial and temporal vegetation sensitivities, leading to biased projections of ecosystem dynamics under future hydro-climatic change.

Wang, Huiqi [University of California, Berkeley, C↗

DOE OSTI2024

Global and regional hydrological impacts of global forest expansion

Abstract. Large-scale reforestation, afforestation, and forest restoration schemes have gained global support as climate change mitigation strategies due to their significant carbon dioxide removal (CDR) potential. However, there has been limited research into the unintended consequences of forestation from a biophysical perspective. In the Community Earth System Model version 2 (CESM2), we apply a global forestation scenario, within a Paris Agreement-compatible warming scenario, to investigate the land surface and hydroclimate response. Compared to a control scenario where land use is fixed to present-day levels, the forestation scenario is up to 2 °C cooler at low latitudes by 2100, driven by a 10 % increase in evaporative cooling in forested areas. However, afforested areas where grassland or shrubland are replaced lead to a doubling of plant water demand in some tropical regions, causing significant decreases in soil moisture (∼ 5 % globally, 5 %–10 % regionally) and water availability (∼ 10 % globally, 10 %–15 % regionally) in regions with increased forest cover. While there are some increases in low cloud and seasonal precipitation over the expanded tropical forests, with enhanced negative cloud radiative forcing, the impacts on large-scale precipitation and atmospheric circulation are limited. This contrasts with the precipitation response to simulated large-scale deforestation found in previous studies. The forestation scenario demonstrates local cooling benefits without major disruption to global hydrodynamics beyond those already projected to result from climate change, in addition to the cooling associated with CDR. However, the water demands of extensive forestation, especially afforestation, have implications for its viability, given the uncertainty in future precipitation changes.

Environmental Sciences & Ecology↗

NASA NTRS2021

The Salinity Pilot-Mission Exploitation Platform (Pi-MEP): A Hub for Validation and Exploitation of Satellite Sea Surface Salinity Data

The Pilot-Mission Exploitation Platform (Pi-MEP) for salinity is an ESA initiative originally meant to support and widen the uptake of Soil Moisture and Ocean Salinity (SMOS) mission data over the ocean. Starting in 2017, the project aims at setting up a computational web-based platform focusing on satellite sea surface salinity data, supporting studies on enhanced validation and scientific process over the ocean. It has been designed in close collaboration with a dedicated science advisory group in order to achieve three main objectives: gathering all the data required to exploit satellite sea surface salinity data, systematically producing a wide range of metrics for comparing and monitoring sea surface salinity products’ quality, and providing user-friendly tools to explore, visualize and exploit both the collected products and the results of the automated analyses. The Salinity Pi-MEP is becoming a reference hub for the validation of satellite sea surface salinity missions by providing valuable information on satellite products (SMOS, Aquarius, SMAP), an extensive in situ database (e.g., Argo, thermosalinographs, moorings, drifters) and additional thematic datasets (precipitation, evaporation, currents, sea level anomalies, sea surface temperature, etc.). Co-localized databases between satellite products and in situ datasets are systematically generated together with validation analysis reports for 30 predefined regions. The data and reports are made fully accessible through the web interface of the platform. The datasets, validation metrics and tools (automatic, user-driven) of the platform are described in detail in this paper. Several dedicated scientific case studies involving satellite SSS data are also systematically monitored by the platform, including major river plumes, mesoscale signatures in boundary currents, high latitudes, semi-enclosed seas, and the high-precipitation region of the eastern tropical Pacific. Since 2019, a partnership in the Salinity Pi-MEP project has been agreed between ESA and NASA to enlarge focus to encompass the entire set of satellite salinity sensors. The two agencies are now working together to widen the platform features on several technical aspects, such as triple-collocation software implementation, additional match-up collocation criteria and sustained exploitation of data from the SPURS campaigns

ocean↗

DOE OSTI2024

Are Marine Low Cloud Droplet Concentrations Buffered by Entrained Aitken‐Mode Aerosol (Final Technical Report)

During the summertime, the high-latitude oceans come to life with green phytoplankton, which gain their energy from sunlight and are food for sea creatures small and large. When the phytoplankton are eaten or die, sulfur-rich gases are released under the ocean surface and mix into the air. Observations suggest that, over the Southern Ocean, frequent storms lift this air high into the atmosphere while raining out particulates like salt. As a result, the sulfur-rich air then spawns high concentrations of small ‘Aitken-mode’ aerosol particles. We hypothesize that these particles work their way down into the marine boundary layer, where they can replenish the supply of cloud-condensation nuclei scavenged by frequent precipitation. Further, this process maintains high concentrations of liquid cloud droplets in austral summer, promoting more sunlight to be reflected to space. We call this ‘Aitken buffering’. The primary objective of this project has been to document and test what role Aitken-mode aerosols play in clouds over the Southern Ocean and elsewhere. This effort has included three main components: 1) developing a computer model that realistically simulates the aerosol processes and the small-scale turbulent air motions that move aerosols around and create the clouds, 2) using that model to interpret and extend these observations for process understanding, by allowing different factors that contribute to the aerosol budget, such as surface wind speed, precipitation, surface gas exchange, etc. to be separated, and 3) studying Aitken-mode aerosol and its variability with a focus over the Southern Ocean and Antarctica, using data from Atmospheric Radiation Measurement (ARM) sites and other available observations. Initial computer studies in more idealized conditions found that elevated concentrations of Aitken-mode aerosols above the clouds could help prevent the breakup of those clouds by acting as cloud-condensation nuclei after they were entrained into the cloudy boundary layer. Simulations of a day during the ACE-ENA field campaign showed that Aitken-mode aerosols could also prevent cloud breakup under more realistic conditions. A new method that extracts information about Aitken-mode aerosols from measurements of aerosols onto which cloud droplets can form finds that Aitken-mode aerosols do vary seasonally over the Southern Ocean, with a peak in summertime, as described above. Other work during this project has focused on understanding how patterns of water vapor, clouds and precipitation are coupled within low-lying clouds over the oceans, and also on how cloud droplets cluster within clouds and how the distribution of cloud droplet sizes change as dry air is mixed into clouds, with the latter studies also using observations from ACE-ENA.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Ventenata dubia projected to expand in the western United States despite future novel conditions

Abstract Distributions of both native and invasive species are expected to shift under future climate. Species distribution models (SDMs) are often used to explore future habitats, but sources of uncertainty including novel climate conditions may reduce the reliability of future projections. We explore the potential spread of the invasive annual grass ventenata ( Ventenata dubia ) in the western United States under both current and future climate scenarios using boosted regression tree models and 30 global climate models (GCMs). We quantify novel climate conditions, prediction variability arising from both the SDMs and GCMs, and the agreement among GCMs. Results demonstrate that currently suitable habitat is concentrated inside the invaded range of the northwest, but substantial habitat exists outside the invaded range in the Southern Rockies and southwestern US mountains. Future suitability projections vary greatly among GCMs, but GCMs commonly projected decreased suitability in the invaded range and increased suitability along higher elevations of interior mountainous areas. Climate novelty did not appear to undermine the prediction reliability in many cases where the climate–species relationship was fully represented by the occurrence data. GCM‐derived variability resulting from variation in future cool season precipitation and temperature seasonality was greatest in the Rocky Mountains. SDM‐derived variability was higher in currently suitable habitat, and few GCMs projections agreed that these areas would contain future suitable habitat. However, while prediction variability was high, many GCM projections agreed that parts of the Rocky, Wasatch, and Uinta Mountains would contain highly suitable habitat in the future. As disturbances in the interior mountains occur in coming decades, reducing some natural barriers to invasion, land managers, and conservationists will need to monitor for ventenata in post‐disturbance environments. Changes to invasion potential may not play out for several decades, but results related to current potential may have applications for early detection and rapid response planning.

Environmental Sciences & Ecology↗

DOE OSTI2023

A Sustainable and Environmentally Friendly Concrete for Structural Applications

The purpose of this study is to utilize waste products—precipitated calcium carbonate (PCC) and upcycled recycled concrete aggregate (upcycled RCA or UCA)—in civil works projects. To do so, tests must be performed to determine the engineering properties of the materials in which PCC and UCA are sequestered. PCC is a fine to coarse grain waste product generated during the production of sugar from sugar beets. UCA is produced from demolished and returned concrete by the extraction of primarily calcium and alkalinity. The study also includes the use of both PCC and UCA in the same concrete mix design. The test results on PCC alone show that the optimum content to achieve a minimum 28 MPa (4000 psi) compressive strength is 25% and 30%. The corresponding compressive strength of mixes in which conventional aggregate was replaced by UCA is about 48 MPa (7000 psi) to 55 MPa (8000 psi) at the same water: cement ratio (0.44) by weight. The compressive strength of concrete with 25% to 30% cement replaced by PCC and varying aggregates replaced with UCA ranges from 19.3 to 40 MPa (2800 to 5800 psi). Other tests on PCC and UCA include tensile strength of 2 to 3 MPa (293 to 423 psi) and flexural strength of 1.3 to 1.9 MPa (183 to 279 psi). Analytical techniques such as X-ray diffraction (XRD), energy-dispersive X-ray spectrometry (EDX), and scanning electron microscopy (SEM) were used to identify the constituent elements and chemical compounds present in PCC, including calcium carbonate and silica. Based on the test results, the composition of PCC by weight indicates 45.9% calcium, 39.4% oxygen, and 9.2% carbon. Based on the results of this study, we can expect to reduce carbon emissions in the production of cement and aggregates, as well as utilize waste products in the civil engineering field.

42 ENGINEERING↗

DOE OSTI2025

Complementing Dynamical Downscaling With Super‐Resolution Convolutional Neural Networks

Despite advancements in Artificial Intelligence (AI) methods for climate downscaling, significant challenges remain for their practicality in climate research. Current AI-methods exhibit notable limitations, such as limited application in downscaling Global Climate Models (GCMs), and accurately representing extremes. To address these challenges, we implement an AI-based methodology using super-resolution convolutional neural networks (SRCNN), trained and evaluated on 40 years of daily precipitation data from a reanalysis and a high-resolution dynamically downscaled counterpart. The dynamical downscaled simulations, constrained using spectral nudging, enable the replication of historical events at a higher resolution. This allows the SRCNN to emulate dynamical downscaling effectively. Modifications, such as incorporating elevation data and data pre-processing enhances overall model performance, while using exponential and quantile loss functions improve the simulation of extremes. Our findings show SRCNN models efficiently and skillfully downscale precipitation from GCMs. Future work will expand this methodology to downscale additional variables for future climate projections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Two Large-Scale Meteorological Patterns are Associated with Short-Duration Dry Spells in the Northeastern United States

Large-scale meteorological pattern (LSMP)–based analysis is used in a novel way to understand meteorological conditions before and during short-duration dry spells over the northeastern United States. These LSMPs are useful to assess models and select better-performing models for future projections. Dry-spell events are identified from histograms of consecutive dry days below a daily precipitation threshold. Events lasting 12 days or longer, which correspond to ~10% of dry-spell events, are examined. The 500-hPa stream-function anomaly fields for the first 12 days of each event are time averaged, and k -means clustering is applied to isolate the dry-spell-related LSMPs. The first cluster has a strong low pressure anomaly over the Atlantic Ocean, southeast of the region, and is more common in winter and spring. The second cluster has strong high pressure over east-central North America and is most common during autumn. Over the region, both clusters have negative specific humidity anomalies, negative integrated vapor transport from the north, and subsidence associated with a midlatitude jet stream dipole structure that reinforces upper-level convergence. Subsidence is supported by cold-air advection in the first cluster and the location on the east side of the lower-level high pressure in the second cluster. Extratropical cyclone storm tracks are generally shifted southward of the region during the dry spells. Individual events lie on a continuum between two distinct clusters. These clusters have similar local, but different remote, properties. Although dry spells occur with greater frequency during drought months, most dry spells occur during nondrought months. Significance Statement: This study examines the large-scale weather patterns and meteorological conditions associated with dry-spell events lasting at least 2 weeks while affecting the northeastern United States. A statistical approach groups events together on the basis of similar atmospheric features. We find two distinct sets of patterns that we call large-scale meteorological patterns. These patterns reduce moisture, foster localized sinking, and shift the storm track southward along the Atlantic seaboard, all of which reduce precipitation. Besides greater understanding, knowing the meteorological patterns during short-term dryness in the region provides an important tool to assess how well atmospheric models reproduce these specific patterns. More dry spells occur in non-drought months than in drought months, which means that dry spells can occur without preexisting drought conditions.

58 GEOSCIENCES↗

DOE OSTI2020

Efficiency of Room Air Cleaners for Removal of Bioaerosols From Ambient Air

The COVID-19 pandemic necessitated the evaluation of commercial air purification units to protect worker safety in indoor spaces. This project evaluated the efficacy of commercial off-the-shelf air purification systems that utilize electrostatic precipitation for the collection and removal of particulates (including bioaerosols) from ambient air. An aerosol mist containing Escherichia coli (E. coli) and bacteriophage surrogate virus, MS2, was produced using a nebulizer and delivered to the front intake of the commercial system with the ionizer ON and OFF. Removal efficiency was evaluated by colony/plaque formation assays using a small agar plate (60 X 15 mm) to passively collect E. coli and MS2 exhausting from the electrostatic precipitation cell. The system was determined to remove 98-99% of the microorganism introduced to the system. Testing was performed with all pre- and post-electrostatic cell filters removed so further removal is anticipated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2004

"Hot Spots" of Land Atmosphere Coupling

Previous estimates of land-atmosphere interaction (the impact of soil moisture on precipitation) have been limited by a severe paucity of relevant observational data and by the model-dependence of the various computational estimates. To counter this limitation, a dozen climate modeling groups have recently performed the same highly-controlled numerical experiment as part of a coordinated intercomparison project. This allows, for the first time ever, a superior multi-model approach to the estimation of the regions on the globe where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer. Such estimation has many potential benefits; it can contribute, for example, to seasonal rainfall prediction efforts.

Koster, Randal D.↗

NASA NTRS2015

AgMIP Climate Data and Scenarios for Integrated Assessment

Climate change presents a great challenge to the agricultural sector as changes in precipitation, temperature, humidity, and circulation patterns alter the climatic conditions upon which many agricultural systems rely. Projections of future climate conditions are inherently uncertain owing to a lack of clarity on how society will develop, policies that may be implemented to reduce greenhouse-gas (GHG) emissions, and complexities in modeling the atmosphere, ocean, land, cryosphere, and biosphere components of the climate system. Global climate models (GCMs) are based on well-established physics of each climate component that enable the models to project climate responses to changing GHG concentration scenarios (Stocker et al., 2013).The most recent iteration of the Coupled Model Intercomparison Project (CMIP5; Taylor et al., 2012) utilized representative concentration pathways (RCPs) to cover the range of plausible GHG concentrations out past the year 2100, with RCP8.5 representing an extreme scenario and RCP4.5 representing a lower concentrations scenario (Moss et al., 2010).

agriculture↗