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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

The Impact of Satellite Sea Surface Salinity for Prediction of the Coupled Indo-Pacific System

We assess the impact of satellite sea surface salinity (SSS) observations on seasonal to interannual variability of tropical Indo-Pacific Ocean dynamics as well as on dynamical ENSO forecasts. Our coupled model is composed of a primitive equation ocean model for the tropical Indo-Pacific region that is coupled with the global SPEEDY atmospheric model (Molteni, 2003). The Ensemble Reduced Order Kalman Filter is used to assimilate observations to constrain dynamics and thermodynamics for initialization of the coupled model. The baseline experiment assimilates satellite sea level, SST, and in situ subsurface temperature and salinity observations. This baseline is then compared with experiments that additionally assimilate Aquarius (version 4.0) and SMAP (version 2.0) SSS. Twelve-month forecasts are initialized for each month from Sep. 2011 to Dec. 2016. We find that including satellite SSS significantly improves NINO3.4 sea surface temperature anomaly validation after 1 out to 12 month forecast lead times. For initialization of the coupled forecast, the positive impact of SSS assimilation is brought about by surface freshening near the eastern edge of the western Pacific warm pool and density changes that lead to shallower mixed layer between 10S-5N. SST differences at initialization force wide-spread downwelling favorable curl over most of the tropical Pacific. Over an average forecast, SST remains warmer with SSS assimilation at the eastern edge of the warm pool. This warm SST propagates into the eastern Pacific and drags westerly wind anomalies eastward into the NINO3.4 region. In addition, salting near the ITCZ leads to a deepening of the mixed layer and thermocline near 8N. These patterns together lead to a funneling effect that provides the background state to amplify equatorial Kelvin waves. We show that the downwelling Kelvin waves are amplified by assimilating satellite SSS and lead to significantly improved forecasts particularly for the 2015 El Nino.

SST↗
DOE OSTI2020

Climate change and the future productivity and distribution of crab in the Bering Sea

Crab populations in the eastern Bering Sea support some of the most valuable fisheries in the United States, but their future productivity and distribution are uncertain. Here, we explore observed changes in the productivity and distribution for snow crab, Tanner crab, and Bristol Bay red king crab. We link historical indices of environmental variation and predator biomass with observed time series of centroids of abundance and extent of crab stock distribution; we also fit stock–recruit curves including environmental indices for each stock. We then project these relationships under forcing from global climate models to forecast potential productivity and distribution scenarios. Our results suggest that the productivity of snow crab is negatively related to the Arctic Oscillation (AO) and positively related to ice cover; Tanner crab’s productivity and distribution are negatively associated with cod biomass and sea surface temperature. Aspects of red king crab distribution and productivity appear to be related to bottom temperature, ice cover, the AO, and/or cod biomass. Projecting these relationships forward with available forecasts suggests that Tanner crab may become more productive and shift further offshore, red king crab distribution may contract and move north, and productivity may decrease for snow crab as the population contracts northward.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Application of an Embedded Fracture and Borehole Modeling Approach to the Understanding of EGS Collab Experiment 1

EGS Collab is a series of meso-scale experiments and associated numerical simulation activities being funded by the United States Department of Energy, Geothermal Technologies Office (GTO) to investigate enhanced geothermal system processes under in-situ stress and slightly elevated temperature conditions. This project is designed to provide scientists and engineers with immediate access to impermeable rock at scales larger than possible in the laboratory, but generally smaller than those for commercial production. Immediate access to rock is provided via the existing drifts of the former Homestake Gold Mine, now operated as the Sanford Underground Research Facility in Lead, South Dakota. The objectives of the EGS Collab project are to develop well controlled fracture networks between injector and producer boreholes using normal and shear stimulation for permeability enhancement. The first experimental site was located off the West Access drift on the 4850 Level (4850 feet below ground surface) in phyllite of the Precambrian Poorman formation, and involved the creation of a fracture network comprising a combination of hydraulic and natural fractures. A second experimental site is now being considered near the battery alcove on the 4100 Level in amphibolite and rhyolite of the Yates Unit. Data generated during these experiments will be compared against predictions of a suite of computer codes specifically designed to solve problems involving coupled thermal, hydrological, geomechanical, and geochemical processes. Comparisons between experimental and numerical simulation results will provide code developers with direction for improvements and verification of process models, build confidence in the suite of available numerical tools, and ultimately identify critical future development needs for the geothermal modeling community. Moreover, conducting thorough comparisons of models, modelling approaches, measurement approaches and measured data, via the EGS Collab project, will serve to identify techniques that are most likely to succeed at the Frontier Observatory for Research in Geothermal Energy (FORGE), the GTO’s flagship EGS research effort. Experiment 1 has comprised a series of successful tests, including a long-term chilled-water circulation test, but the testbed has two atypical EGS elements. Active ventilation in the adjacent drift over a 50-year period cooled the testbed rock mass and hydraulic fracturing intersected monitoring boreholes making them conduits for fluid flow. Numerical simulations executed in support of the design of the EGS Collab Experiment 1, computed a radial temperature distribution and stress gradient orthogonal to the drift axis, resulting in the forecast of an oblong hydraulic fracture geometry, extended in the direction of the drift from the stimulation borehole. This paper describes the numerical simulation of long-term chilled-water circulation test with an embedded fracture and borehole modeling approach. The principal objective of the simulation work is show agreement between experimental observations in terms of production fluid temperatures, monitoring borehole temperatures, injection and production pressures, and tracer recoveries using a single conceptual model for the fracture network, using characterization and monitoring data generally available for EGS. A secondary objective is to improve the numerical simulation result comparisons with additional data available from the broader monitoring equipment within the testbed versus deeper, hotter, and more remote EGS. One complicating factor for comparisons between the numerical simulation results and experimental observations, is the Joule-Thomson heating associated with large pressure drops across the fracture network.

numerical simulation, embedded fractures and boreh↗
NASA NTRS1977

Deriving mesoscale temperature and moisture fields from satellite radiance measurements over the United States

The ability to provide mesoscale temperature and moisture fields from operational satellite infrared sounding radiances over the United States is explored. High-resolution sounding information for mesoscale analysis and forecasting is shown to be obtainable in mostly clear areas. An iterative retrieval algorithm applied to NOAA-VTPR radiances uses a mean radiosonde sounding as a best initial-guess profile. Temperature soundings are then retrieved at a horizontal resolution of about 70 km, as is an indication of the precipitable water content of the vertical sounding columns. Derived temperature values may be biased in general by the initial-guess sounding or in certain areas by the cloud correction technique, but the resulting relative temperature changes across the field when not contaminated by clouds will be useful for mesoscale forecasting and models. The derived moisture, affected only by high clouds, proves to be reliable to within 0.5 cm of precipitable water and contains valuable horizontal information. Present-day applications from polar-orbiting satellites as well as possibilities from upcoming temperature and moisture sounders on geostationary satellites are noted.

Hillger, D. W.↗
NASA NTRS2018

The Impact of Satellite Sea Surface Salinity for Prediction of the Coupled Indo-Pacific System

We assess the impact of satellite sea surface salinity (SSS) observations on seasonal to interannual variability of tropical Indo-Pacific Ocean dynamics as well as on dynamical ENSO forecasts. Our coupled model is composed of a primitive equation ocean model for the tropical Indo-Pacific region that is coupled with the global SPEEDY atmospheric model (Molteni, 2003). The Ensemble Reduced Order Kalman Filter is used to assimilate observations to constrain dynamics and thermodynamics for initialization of the coupled model. The baseline experiment assimilates satellite sea level, SST, and in situ subsurface temperature and salinity observations. This baseline is then compared with experiments that additionally assimilate Aquarius (version 4.0) and SMAP (version 2.0) SSS. Twelve-month forecasts are initialized for each month from Sep. 2011 to Dec. 2016. We find that including satellite SSS significantly improves NINO 3.4 sea surface temperature anomaly validation after 1 out to 12 month forecast lead times. For initialization of the coupled forecast, the positive impact of SSS assimilation is brought about by surface freshening near the eastern edge of the western Pacific warm pool and density changes that lead to shallower mixed layer between 10 degrees South latitude-5 degrees North latitude. SST differences at initialization force wide-spread downwelling favorable curl over most of the tropical Pacific. Over an average forecast, SST remains warmer with SSS assimilation at the eastern edge of the warm pool. This warm SST propagates into the eastern Pacific and drags westerly wind anomalies eastward into the NINO 3.4 region. In addition, salting near the ITCZ (Intertropical Convergence Zone) leads to a deepening of the mixed layer and thermocline near 8 degrees North latitude. These patterns together lead to a funneling effect that provides the background state to amplify equatorial Kelvin waves. We show that the downwelling Kelvin waves are amplified by assimilating satellite SSS and lead to significantly improved forecasts particularly for the 2015 El Nino.

El Nino↗
DOE OSTI2024

Multi-year assessment of the impact of ship-borne radiosonde observations on polar WRF forecasts in the Arctic

Abstract To compensate for the lack of conventional observations over the Arctic Ocean, ship-borne radiosonde observations have been regularly carried out during summer Arctic expeditions and the observed data have been broadcast via the global telecommunication system since 2017. With these data obtained over the data-sparse Arctic Ocean, observing system experiments were carried out using a polar-optimized version of the Weather Research and Forecasting (WRF) model and the WRF Data Assimilation (WRFDA) system to investigate their effects on analyses and forecasts over the Arctic. The results of verification against reanalysis data reveal: (1) DA effects on analyses and forecasts; (2) the reason for the year-to-year variability of DA effects; and (3) the possible role of upper-level potential vorticity in delayed DA effects. The overall assimilation effects of the extra data on the analyses and forecasts over the Arctic are positive. Initially, the DA effects are the most apparent in the temperature variables in the middle/lower troposphere, which spread to the wind variables in the upper troposphere. The effects decrease with time but reappear after approximately 120 h, even in the 240-h forecasts. The effects on forecasts vary depending on the proximity of the radiosonde observation locations to the high synoptic variability. The upper-level potential vorticity is known to play an important role in the development of Arctic cyclones, and it is suggested as a possible explanation for the delayed DA effects after about 120 h.

Geology↗
DOE OSTI2024

Effects of hurricane disturbance and increased temperature on carbon cycling and storage of a Puerto Rican forest: a mechanistic investigation of above- and belowground processes (Final Technical Report)

The overall goal of the Tropical Responses for Altered Climate Experiment (TRACE) is to assess the effects of increasing temperature on tropical plant and soil carbon fluxes and storage as the forest recovers from major hurricane disturbance that occurred in September 2017. Ultimately, we aimed to reduce uncertainty and increase confidence with which tropical forests are represented in Earth System models to make more accurate global forecasts of future climate. We focused on both above- and belowground processes and explored temperature controls over critical aspects of carbon and nutrient cycling for tropical plants, soil, and microbes. TRACE is located in a wet tropical forest in the Luquillo Experimental Forest close to the USDA Forest Service Sabana Field Research Station in Luquillo, Puerto Rico. The warming treatment consists of six 4.7 m diameter plots. Three of the plots receive infrared warming and three have the same infrastructure but are not warmed (using ‘dummy’ heaters). Each plot was monitored from 2018-2023 to investigate two major questions: 1) Are there legacy effects of prior warming on forest recovery following hurricane disturbance? 2) Will the trajectory of forest recovery following disturbance be affected by warmer temperatures? Concurrent soil incubation experiments were conducted to enable more controlled mechanistic investigations of temperature response on microbial function. In sum, our goal was to use this novel climate manipulation experiment (the only of its kind in any tropical forest) and once-in-a-lifetime chance to assess how temperature and hurricane disturbance interact to affect coupled biogeochemical cycling in a tropical forest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Moving lens effect: Simulations, forecasts, and foreground mitigation

The peculiar motion of massive objects across the line of sight imprints a dipolar temperature anisotropy pattern on the cosmic microwave background known as the moving lens effect. This effect provides a unique probe of the transverse components of the peculiar velocity field, but has not yet been detected due to its small size. We implement and validate a stacking estimator for the moving lens signal using a galaxy catalog as a tracer of massive haloes combined with reconstructed velocities from the galaxy number density field. Using simulations, we forecast detection prospects for the moving lens signal from current and upcoming microwave background and galaxy surveys. Here, we demonstrate a new foreground mitigation strategy likely sufficient for current datasets, and discuss various sources of systematic error and noise. Upcoming galaxy surveys will provide high-significance statistical detections of the moving lens effect.

Astrophysical & cosmological simulations↗
NASA NTRS2012

On the Influence of North Pacific Sea Surface Temperature on the Arctic Winter Climate

Differences between two ensembles of Goddard Earth Observing System Chemistry-Climate Model simulations isolate the impact of North Pacific sea surface temperatures (SSTs) on the Arctic winter climate. One ensemble of extended winter season forecasts is forced by unusually high SSTs in the North Pacific, while in the second ensemble SSTs in the North Pacific are unusually low. High Low differences are consistent with a weakened Western Pacific atmospheric teleconnection pattern, and in particular, a weakening of the Aleutian low. This relative change in tropospheric circulation inhibits planetary wave propagation into the stratosphere, in turn reducing polar stratospheric temperature in mid- and late winter. The number of winters with sudden stratospheric warmings is approximately tripled in the Low ensemble as compared with the High ensemble. Enhanced North Pacific SSTs, and thus a more stable and persistent Arctic vortex, lead to a relative decrease in lower stratospheric ozone in late winter, affecting the April clear-sky UV index at Northern Hemisphere mid-latitudes.

Hurwitz, Margaret M.↗
NASA NTRS2012

Receivers Gather Data for Climate, Weather Prediction

Signals from global positioning system (GPS) satellites are now being used for more than just location and navigation information. By looking at the radio waves from GPS satellites, a technology developed at NASA s Jet Propulsion Laboratory (JPL) not only precisely calculates its position, but can also use a technique known as radio occultation to help scientists study the Earth s atmosphere and gravity field to improve weather forecasts, monitor climate change, and enhance space weather research. The University Corporation for Atmospheric Research (UCAR), a nonprofit group of universities in Boulder, Colorado, compares radio occultation to the appearance of a pencil when viewed though a glass of water. The water molecules change the path of visible light waves so that the pencil appears bent, just like molecules in the air bend GPS radio signals as they pass through (or are occulted by) the atmosphere. Through measurements of the amount of bending in the signals, scientists can construct detailed images of the ionosphere (the energetic upper part of the atmosphere) and also gather information about atmospheric density, pressure, temperature, and moisture. Once collected, this data can be input into weather forecasting and climate models for weather prediction and climate studies. Traditionally, such information is obtained through the use of weather balloons. In 1998, JPL started developing a new class of GPS space science receivers, called Black Jack, that could take precise measurements of how GPS signals are distorted or delayed along their way to the receiver. By 2006, the first demonstration of a GPS radio occultation constellation was launched through a collaboration among Taiwan s National Science Council and National Space Organization, the U.S. National Science Foundation, NASA, the National Oceanic and Atmospheric Administration (NOAA), and other Federal entities. Called the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), JPL was responsible for designing COSMIC s primary instrument - based on its revolutionary Black Jack receiver.

Source record↗
NASA NTRS2018

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO S2S Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite Sea Surface Salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (National Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF ( Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive) V4 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by the satellite at approximately 1 centimeter) and in situ measurements (typically measured by Argo floats at 3 meters). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from the GMAO S2S reanalyses that assimilates/withholds along-track (L2) SSS. In particular, we contrast forecasts of the overestimated 2014 El Nino, the big 2015 El Nino, and the minor 2016 La Nina. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrades the mixed layer depth leading to more accurate coupled air/sea interaction.

Hackert, E.↗
NASA NTRS2019

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO Seasonal Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite sea surface salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (North American Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF (Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive satellite) V4.1 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by satellite at approximately 1-centimeter depth) and in situ measurements (typically measured by Argo floats at 3-meters depth). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from GMAO S2S spring reanalyses that assimilate/withhold along-track (L2) SSS. In particular, we contrast forecasts of the big 2015 El Nino, the 2017 La Nina and the 2018 weak El Nino. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrade the mixed layer depth leading to more accurate coupled air/sea interaction. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP, allows a unique opportunity to compare and contrast forecasts initialized with the benefit of these two satellite SSS observation types. We assess the impact of gridded satellite sea surface salinity observations on dynamical ENSO forecasts for the big 2015 El Nino.

Hackert, E.↗
NASA NTRS1976

Mesoscale temperature and moisture fields from satellite infrared soundings

The combined use of radiosonde and satellite infrared soundings can provide mesoscale temperature and moisture fields at the time of satellite coverage. Radiance data from the vertical temperature profile radiometer on NOAA polar-orbiting satellites can be used along with a radiosonde sounding as an initial guess in an iterative retrieval algorithm. The mesoscale temperature and moisture fields at local 9 - 10 a.m., which are produced by retrieving temperature profiles at each scan spot for the BTPR (every 70 km), can be used for analysis or as a forecasting tool for subsequent weather events during the day. The advantage of better horizontal resolution of satellite soundings can be coupled with the radiosonde temperature and moisture profile both as a best initial guess profile and as a means of eliminating problems due to the limited vertical resolution of satellite soundings.

Hillger, D. W.↗
NASA NTRS2001

Ground-Based Icing Condition Remote Sensing System Definition

This report documents the NASA Glenn Research Center activities to assess and down select remote sensing technologies for the purpose of developing a system capable of measuring icing condition hazards aloft. The information generated by such a remote sensing system is intended for use by the entire aviation community, including flight crews. air traffic controllers. airline dispatchers, and aviation weather forecasters. The remote sensing system must be capable of remotely measuring temperature and liquid water content (LWC), and indicating the presence of super-cooled large droplets (SLD). Technologies examined include Profiling Microwave Radiometer, Dual-Band Radar, Multi-Band Radar, Ka-Band Radar. Polarized Ka-Band Radar, and Multiple Field of View (MFOV) Lidar. The assessment of these systems took place primarily during the Mt. Washington Icing Sensors Project (MWISP) in April 1999 and the Alliance Icing Research Study (AIRS) from November 1999 to February 2000. A discussion of the various sensing technologies is included. The result of the assessment is that no one sensing technology can satisfy all of the stated project goals. Therefore a proposed system includes radiometry and Ka-band radar. A multilevel approach is proposed to allow the future selection of the fielded system based upon required capability and available funding. The most basic level system would be the least capable and least expensive. The next level would increase capability and cost, and the highest level would be the most capable and most expensive to field. The Level 1 system would consist of a Profiling Microwave Radiometer. The Level 2 system would add a Ka-Band Radar. The Level 3 system would add polarization to the Ka-Band Radar. All levels of the system would utilize hardware that is already under development by the U.S. Government. However, to meet the needs of the aviation community, all levels of the system will require further development. In addition to the proposed system, it is also recommended that NASA continue to foster the development of Multi-Band Radar and airborne microwave radiometer technologies.

Reehorst, Andrew L.↗
NASA NTRS2017

Dynamical Conditions of Ice Supersaturation and Ice Nucleation in Convective Systems: A Comparative Analysis Between in Situ Aircraft Observations and WRF Simulations

Occurrence frequency and dynamical conditions of ice supersaturation (ISS, where relative humidity with respect to ice (RHi) greater than 100%) are examined in the upper troposphere around convective activity. Comparisons are conducted between in situ airborne observations and the Weather Research and Forecasting model simulations using four double-moment microphysical schemes at temperatures less than or or equal to -40degdegC. All four schemes capture both clear-sky and in-cloud ISS conditions. However, the clear-sky (in-cloud) ISS conditions are completely (significantly) limited to the RHi thresholds of the Cooper parameterization. In all of the simulations, ISS occurrence frequencies are higher by approximately 3-4 orders of magnitude at higher updraft speeds (greater than 1 m s(exp -1) than those at the lower updraft speeds when ice water content (IWC) greater than 0.01 gm(exp -3), while observations show smaller differences up to approximately 1-2 orders of magnitude. The simulated ISS also occurs less frequently at weaker updrafts and downdrafts than observed. These results indicate that the simulations have a greater dependence on stronger updrafts to maintain/generate ISS at higher IWC. At lower IWC (less than or equal or 0.01 gm(exp -3), simulations unexpectedly show lower ISS frequencies at stronger updrafts. Overall, the Thompson aerosol-aware scheme has the closest magnitudes and frequencies of ISS greater than 20% to the observations, and the modified Morrison has the closest correlations between ISS frequencies and vertical velocity at higher IWC and number density. The Cooper parameterization often generates excessive ice crystals and therefore suppresses the frequency and magnitude of ISS, indicating that it should be initiated at higher ISS (e.g.,lees than or equal to 25%).

D’Alessandro, John J.↗
NASA NTRS2021

Evaluation of Global Surface Water Temperature Data Sets for use in Passive Remote Sensing of Soil Moisture

Inland open water bodies often pose a systematic error source in the passive remote sensing retrievals of soil moisture. Water temperature is a necessary variable used to compute water emissions that is required to be subtracted from satellite observation to yield actual emissions from the land portion, which in turn generates accurate soil moisture retrievals. Therefore, overestimation of soil moisture can often be corrected using concurrent water temperature data in the overall mitigation procedure. In recent years, several data sets of lake water temperature have become available, but their specifications and accuracy have rarely been investigated in the context of passive soil moisture remote sensing on a global scale. For this reason, three lake temperature products were evaluated against in-situ measurements from 2007 to 2011. The data sets include the lake surface water temperature (LSWT) from Global Observatory of Lake Responses to Environmental Change (GloboLakes), the Copernicus Global Land Operations Cryosphere and Water (C-GLOPS), as well as the lake mix-layer temperature (LMLT) from the European Centers for Medium-Range Weather Forecast (ECMWF) ERA5 Land Reanalysis. GloboLakes, C-GLOPS, and ERA5 Land have overall comparable performance with Pearson correlations (R) of 0.87, 0.92 and 0.88 in comparison with in-situ measurements. LSWT products exhibit negative median biases of −0.27 K (GloboLakes) and −0.31 K (C-GLOPS), whereas the median bias of LMLT is 1.56 K. When mapped from their respective native resolutions to a common 9 km Equal-Area Scalable Earth (EASE) Grid 2.0 projection, similar relative performance was observed. LMLT and LSWT data are closer in performance over the 9 km grid cells that exhibit a small range of lake cover fractions (0.05–0.5). Despite comparable relative performance, ERA5 Land shows great advantages in spatial coverage and temporal resolution. In summary, an integrated evaluation on data accuracy, long-term availability, global coverage, temporal resolution, and regular forward processing with modest data latency led us to conclude that LMLT from the ERA5 Land Reanalysis product represents the most optimal path for use in the development of a long-term soil moisture product.

Runze Zhang↗
NASA NTRS2007

The Impact of Atmospheric InfraRed Sounder (AIRS) Profiles on Short-term Weather Forecasts

The Atmospheric Infrared Sounder (AIRS), together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced spacebased atmospheric sounding systems. The combined AlRS/AMSU system provides radiance measurements used to retrieve temperature profiles with an accuracy of 1 K over 1 km layers under both clear and partly cloudy conditions, while the accuracy of the derived humidity profiles is 15% in 2 km layers. Critical to the successful use of AIRS profiles for weather and climate studies is the use of profile quality indicators and error estimates provided with each profile Aside form monitoring changes in Earth's climate, one of the objectives of AIRS is to provide sounding information of sufficient accuracy such that the assimilation of the new observations, especially in data sparse region, will lead to an improvement in weather forecasts. The purpose of this paper is to describe a procedure to optimally assimilate highresolution AIRS profile data in a regional analysis/forecast model. The paper will focus on the impact of AIRS profiles on a rapidly developing east coast storm and will also discuss preliminary results for a 30-day forecast period, simulating a quasi-operation environment. Temperature and moisture profiles were obtained from the prototype version 5.0 EOS science team retrieval algorithm which includes explicit error information for each profile. The error profile information was used to select the highest quality temperature and moisture data for every profile location and pressure level for assimilation into the ARPS Data Analysis System (ADAS). The AIRS-enhanced analyses were used as initial fields for the Weather Research and Forecast (WRF) system used by the SPORT project for regional weather forecast studies. The ADASWRF system will be run on CONUS domain with an emphasis on the east coast. The preliminary assessment of the impact of the AIRS profiles will focus on quality control issues associated with AIRS, intelligent use of the quality indicators, and forecast verification.

Chou, Shih-Hung↗
NASA NTRS2019

Impact of Aquarius and SMAP Satellite Sea Surface Salinity Observations on Coupled El Niño/Southern Oscillation Forecasts

This study demonstrates the positive impact of including gridded Aquarius and SMAP sea surface salinity (SSS) into initialization of coupled forecasts for the tropical Indo-Pacific. An experiment that assimilates conventional ocean observations serves as the control. In a separate experiment, Aquarius and SMAP satellite SSS are additionally assimilated into the control initialization. Analysis of the initialization differences with the control indicates that SSS assimilation causes a freshening and shallowing of the mixed layer depth (MLD) near the equator and enhanced Kelvin wave amplitude. For each month from September 2011 to September 2018, 12 month coupled ENSO forecasts are initialized from both the control and satellite SSS assimilation experiments. The experiment assimilating Aquarius and SMAP SSS significantly outperforms the control relative to observed NINO3.4 sea surface temperature anomalies. This work highlights the importance of inclusion of satellite SSS for improving the initialization ENSO coupled forecasts.

Hackert, Eric C.↗