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NASA NTRS2017

Image Detective 2.0: Engaging Citizen Scientists with NASA Astronaut Photography

Image Detective 2.0 engages citizen scientists with NASA astronaut photography of the Earth obtained by crew members on the International Space Station (ISS). Engaged citizen scientists are helping to build a more comprehensive and searchable database by geolocating this imagery and contributing to new imagery collections. Image Detective 2.0 is the newest addition to the suite of citizen scientist projects available through CosmoQuest, an effort led by the Astronomical Society of the Pacific (ASP) and supported through a NASA Science Mission Directorate Cooperative Agreement Notice award. CosmoQuest hosts a number of citizen science projects enabling individuals from around the world to engage in authentic NASA science. Image Detective 2.0, an effort that focuses on imagery acquired by astronauts on the International Space Station, builds on work initiated in 2012 by scientists and education specialists at the NASA Johnson Space Center. Through the many lessons learned, Image Detective 2.0 enhances the original project by offering new and improved options for participation. Existing users, as well as new Image Detective participants joining through the CosmoQuest platform, gain first-hand experience working with astronaut photography and become more engaged with this valuable data being obtained from the International Space Station. Citizens around the world are captivated by astronauts living and working in space. As crew members have a unique vantage point from which to view our Earth, the Crew Earth Observations (CEO) online database, referred to as the Gateway to Astronaut Photography of Earth (https://eol.jsc.nasa.gov/), provides a means for crew members to share their unique views of our home planet from the ISS with the scientific community and the public. Astronaut photography supports multiple uses including scientific investigations, visualizations, education, and outreach. These astronaut images record how the planet is changing over time, from human-made changes like urban growth and agriculture, to natural features and landforms such as tropical cyclones, aurora, coastlines, volcanoes and more. This imagery provides researchers on Earth with data to understand the planet from the perspective of the ISS, and is a useful complement to other remotely sensed datasets collected from robotic satellite platforms.

Higgins, Melissa↗
NASA NTRS2017

Synoptic Traveling Weather Systems on Mars: Effects of Radiatively-Active Water Ice Clouds

Atmospheric aerosols on Mars are critical in determining the nature of its thermal structure, its large-scale circulation, and hence the overall climate of the planet. We conduct multi-annual simulations with the latest version of the NASA Ames Mars global climate model (GCM), gcm2.3+, that includes a modernized radiative-transfer package and complex water-ice cloud microphysics package which permit radiative effects and interactions of suspended atmospheric aerosols (e.g., water ice clouds, water vapor, dust, and mutual interactions) to influence the net diabatic heating. Results indicate that radiatively active water ice clouds profoundly affect the seasonal and annual mean climate. The mean thermal structure and balanced circulation patterns are strongly modified near the surface and aloft. Warming of the subtropical atmosphere at altitude and cooling of the high latitude atmosphere at low levels takes place, which increases the mean pole-to-equator temperature contrast (i.e., "baroclinicity"). With radiatively active water ice clouds (RAC) compared to radiatively inert water ice clouds (nonRAC), significant changes in the intensity of the mean state and forced stationary Rossby modes occur, both of which affect the vigor and intensity of traveling, synoptic period weather systems.Such weather systems not only act as key agents in the transport of heat and momentum beyond the extent of the Hadley circulation, but also the transport of trace species such as water vapor, water ice-clouds, dust and others. The northern hemisphere (NH) forced Rossby waves and resultant wave train are augmented in the RAC case: the modes are more intense and the wave train is shifted equatorward. Significant changes also occur within the subtropics and tropics. The Rossby wave train sets up, combined with the traveling synoptic period weather systems (i.e., cyclones and anticyclones), the geographic extent of storm zones (or storm tracks) within the NH. A variety of circulation features will be presented which indicate contrasts between the RAC and nonRAC cases, and which highlight key effects radiatively-active clouds have on physical and dynamical processes active in the current climate of Mars.

GCM-global climate model↗
NASA NTRS2017

Considerations for Using Hybrid Ensemble-Variational Data Assimilation in NASA-GMAO's Next Reanalysis System

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) is the latest reanalysis produced by GMAO, and provides global data spanning the period 1980-present. The atmospheric data assimilation component of MERRA-2 used a 3D-Var scheme, which was operational at the time of its design. Since then, a Hybrid 3D-Var, then a Hybrid 4D-EnVar were implemented, adding an ensemble component to the data assimilation scheme. In this work, we will be examining the benefits of using hybrid ensemble flow-dependent covariances to represent errors and uncertainties in historic periods. Specifically, periods of pre- and post-satellites, as well as periods of active tropical cyclone seasons. Finally, we will also be exploring the use of adaptive localization scales.

MERRA-↗
NASA NTRS2017

The Extratropical Transition of Tropical Storm Cindy From a GLM, ISS LIS and GPM Perspective

The distribution of lightning with respect to tropical convective precipitation systems has been well established in previous studies and more recently by the successful Tropical Rainfall Measuring Mission (TRMM). However, TRMM did not provide information about precipitation features poleward of +/-38 deg latitude. Hence we focus on the evolution of lightning within extra-tropical cyclones traversing the mid-latitudes, especially its oceans. To facilitate such studies, lightning data from the Geostationary Lightning Mapper (GLM) onboard GOES-16 was combined with precipitation features obtained from the Global Precipitation Measurement (GPM) mission constellation of satellites.

Precipitation↗
NASA NTRS2016

The Impacts of Dry Dynamic Cores on Asymmetric Hurricane Intensification

The fundamental pathways for tropical cyclone (TC) intensification are explored by considering axisymmetric and asymmetric impulsive thermal perturbations to balanced, TC-like vortices using the dynamic cores of three different nonlinear numerical models. Attempts at reproducing the results of previous work, which used the community WRF Model, revealed a discrepancy with the impacts of purely asymmetric thermal forcing. The current study finds that thermal asymmetries can have an important, largely positive role on the vortex intensification, whereas other studies find that asymmetric impacts are negligible. Analysis of the spectral energetics of each numerical model indicates that the vortex response to asymmetric thermal perturbations is significantly damped in WRF relative to the other models. Spectral kinetic energy budgets show that this anomalous damping is primarily due to the increased removal of kinetic energy from the vertical divergence of the vertical pressure flux, which is related to the flux of inertia-gravity wave energy. The increased kinetic energy in the other two models is shown to originate around the scales of the heating and propagate upscale with time from nonlinear effects. For very large thermal amplitudes (50 K), the anomalous removal of kinetic energy due to inertia-gravity wave activity is much smaller, resulting in good agreement between models. The results of this paper indicate that the numerical treatment of small-scale processes that project strongly onto inertia-gravity wave energy can lead to significant differences in asymmetric TC intensification. Sensitivity tests with different time integration schemes suggest that diffusion entering into the implicit solution procedure is partly responsible for the anomalous damping of energy.

Guimond, Stephen R.↗
NASA NTRS2017

H31G-1596: DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remote sensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud shadow mask from geostationary satellite data is critical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds,which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classify cloudshadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoderdecoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multispectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

GOES-1↗
NASA NTRS2017

Extreme Storms

Key Findings: 1. Human activities have contributed substantially to observed ocean-atmosphere variability in the Atlantic Ocean (medium confidence), and these changes have contributed to the observed upward trend in North Atlantic hurricane activity since the 1970s (medium confidence). 2. Both theory and numerical modeling simulations generally indicate an increase in tropical cyclone (TC) intensity in a warmer world, and the models generally show an increase in the number of very intense TCs. For Atlantic and eastern North Pacific hurricanes and western North Pacific typhoons, increases are projected in precipitation rates (high confidence) and intensity (medium confidence). The frequency of the most intense of these storms is projected to increase in the Atlantic and western North Pacific (low confidence) and in the eastern North Pacific (medium confidence). 3. Tornado activity in the United States has become more variable, particularly over the 2000s, with a decrease in the number of days per year with tornadoes and an increase in the number of tornadoes on these days (medium confidence). Confidence in past trends for hail and severe thunderstorm winds, however, is low. Climate models consistently project environmental changes that would putatively support an increase in the frequency and intensity of severe thunderstorms (a category that combines tornadoes, hail, and winds), especially over regions that are currently prone to these hazards, but confidence in the details of this projected increase is low. 4. There has been a trend toward earlier snowmelt and a decrease in snowstorm frequency on the southern margins of climatologically snowy areas (medium confidence). Winter storm tracks have shifted northward since 1950 over the Northern Hemisphere (medium confidence). Projections of winter storm frequency and intensity over the United States vary from increasing to decreasing depending on region, but model agreement is poor and confidence is low. Potential linkages between the frequency and intensity of severe winter storms in the United States and accelerated warming in the Arctic have been postulated, but they are complex, and, to some extent, contested, and confidence in the connection is currently low. 5. The frequency and severity of landfalling "atmospheric rivers" on the U.S. West Coast (narrow streams of moisture that account for 30 percent to 40 percent of the typical snowpack and annual precipitation in the region and are associated with severe flooding events) will increase as a result of increasing evaporation and resulting higher atmospheric water vapor that occurs with increasing temperature. (Medium confidence)

Kossin, J. P.↗
NASA NTRS2017

A Closer Look at the ABI on the GOES-R Series

The Advanced Baseline Imager (ABI) on board the Geostationary Operational Environmental Satellite-R (GOES-R) is America's next-generation geostationary advanced imager. GOES-R launched on 19 November 2016. The ABI is a state-of-the-art 16-band radiometer, with spectral bands covering the visible, near-infrared, and infrared portions of the electromagnetic spectrum. Many attributes of the ABI-such as spectral, spatial, and temporal resolution; radiometrics; and image navigation/registration-are much improved from the current series of GOES imagers. This paper highlights and discusses the expected improvements of each of these attributes. From ABI data many higher-level-derived products can be generated and used in a large number of environmental applications. The ABI's design allows rapid-scan and contiguous U.S. imaging automatically interleaved with full-disk scanning. In this paper the expected instrument attributes are covered, as they relate to signal-to-noise ratio, image navigation and registration, the various ABI scan modes, and other parameters. There will be several methods for users to acquire GOES-R imagery and products depending on their needs. These include direct reception of the imagery via the satellite downlink and an online-accessible archive. The information from the ABI on the GOES-R series will be used for many applications related to severe weather, tropical cyclones and hurricanes, aviation, natural hazards, the atmosphere, the ocean, and the cryosphere.

GOES-R↗
NASA NTRS2018

Hurricane Imaging Radiometer (HIRAD) Wind Speed Retrievals and Assessment Using Dropsondes

The Hurricane Imaging Radiometer (HIRAD) is an experimental C-band passive microwave radiometer designed to map the horizontal structure of surface wind speed fields in hurricanes. New data processing and customized retrieval approaches were developed after the 2015 Tropical Cyclone Intensity (TCI) experiment, which featured flights over Hurricanes Patricia, Joaquin, Marty, and the remnants of Tropical Storm Erika. These new approaches produced maps of surface wind speed that looked more realistic than those from previous campaigns. Dropsondes from the High Definition Sounding System (HDSS) that was flown with HIRAD on a WB-57 high altitude aircraft in TCI were used to assess the quality of the HIRAD wind speed retrievals. The root mean square difference between HIRAD-retrieved surface wind speeds and dropsonde-estimated surface wind speeds was 6.0 meters per second. The largest differences between HIRAD and dropsonde winds were from data points where storm motion during dropsonde descent compromised the validity of the comparisons. Accounting for this and for uncertainty in the dropsonde measurements themselves, we estimate the root mean square error for the HIRAD retrievals as around 4.7 meters per second. Prior to the 2015 TCI experiment, HIRAD had previously flown on the WB-57 for missions across Hurricanes Gonzalo (2014), Earl (2010), and Karl (2010). Configuration of the instrument was not identical to the 2015 flights, but the methods devised after the 2015 flights may be applied to that previous data in an attempt to improve retrievals from those cases.

wind retrieval↗
NASA NTRS2018

The Roles of Climate Change and Climate Variability in the 2017 Atlantic Hurricane Season

The 2017 hurricane season was extremely active with six major hurricanes, the third most on record. The sea-surface temperatures (SSTs) over the eastern Main Development Region (EMDR), where many tropical cyclones (TCs) developed during active months of August/September, were approximately 0.96 degrees Centigrade above the 1901-2017 average (warmest on record): about 0.42 degrees Centigrade from a long-term upward trend and the rest (around 80 percent) attributed to the Atlantic Meridional Mode (AMM). The contribution to the SST from the North Atlantic Oscillation over the EMDR was a weak warming, while that from ENSO was negligible. Nevertheless, ENSO, the NAO, and the AMM all contributed to favorable wind shear conditions, while the AMM also produced enhanced atmospheric instability. Compared with the strong hurricane years of 2005-2010, the ocean heat content (OHC) during 2017 was larger across the tropics, with higher SST anomalies over the EMDR and Caribbean Sea. On the other hand, the dynamical/thermodynamical atmospheric conditions, while favorable for enhanced TC activity, were less prominent than in 2005-2010 across the tropics. The results suggest that unusually warm SST in the EMDR together with the long fetch of the resulting storms in the presence of record-breaking OHC were key factors in driving the strong TC activity in 2017.

SST↗
NASA NTRS2018

The Arctic Sea Ice Cover of 2016: A Year of Record-Low Highs and High-Than-Expected Lows

The Arctic sea ice cover of 2016 was highly noteworthy, as it featured record low monthly sea ice extents at the start of the year but a summer (September) extent that was higher than expected by most seasonal forecasts. Here we explore the 2016 Arctic sea ice state in terms of its monthly sea ice cover, placing this in the context of the sea ice conditions observed since 2000. We demonstrate the sensitivity of monthly Arctic sea ice extent and area estimates, in terms of their magnitude and annual rankings, to the ice concentration input data (using two widely used datasets) and to the averaging methodology used to convert concentration to extent (daily or monthly extent calculations). We use estimates of sea ice area over sea ice extent to analyse the relative “compactness†of the Arctic sea ice cover, highlighting anomalously low compactness in the summer of 2016 which contributed to the higher-than-expected September ice extent. Two cyclones that entered the Arctic Ocean during August appear to have driven this low-concentration/compactness ice cover but were not sufficient to cause more widespread melt-out and a new record-low September ice extent. We use concentration budgets to explore the regions and processes (thermodynamics/ dynamics) contributing to the monthly 2016 extent/area estimates highlighting, amongst other things, rapid ice intensification across the central eastern Arctic through September. Two different products show significant early melt onset across the Arctic Ocean in 2016, including record-early melt onset in the North Atlantic sector of the Arctic. Our results also show record-late 2016 freeze-up in the central Arctic, North Atlantic and the Alaskan Arctic sector in particular, associated with strong sea surface temperature anomalies that appeared shortly after the 2016 minimum (October onwards). We explore the implications of this low summer ice compactness for seasonal forecasting, suggesting that sea ice area could be a more reliable metric to forecast in this more seasonal, "New Arctic", sea ice regime.

sea ice↗
NASA NTRS2018

Sensitivity of Different Types of Observations to NASA GEOS Hurricane Analyses and Forecasts

The 2017 Atlantic hurricane season was the 5th most active, featuring 17 named storms, the highest number of major hurricanes since 2005, and by far the costliest season on record. African easterly waves often serve as the seeding circulation for a large portion of hurricanes (i.e. tropical storms with wind over 74mph in the Atlantic and Northeast Pacific). Warm SST, moist air, and low wind shear are the main requirements for tropical cyclones to develop and maintain hurricane strength. In terms of hurricane propagation (so called hurricane tracks), Atlantic hurricanes typically propagate around the periphery of the subtropical ridge called the Bermuda High (Azores High), riding along its strongest winds. If the high is positioned to the east, then hurricanes generally propagate northeastward around the high's western edge into the open Atlantic Ocean without making land fall. If the high is positioned to the west and extends far enough to the south, storms are blocked from curving north and forced to continue west towards Florida, Cuba, and the Gulf of Mexico. If we have accurate atmospheric temperature distribution, which is directly related to atmospheric wave patterns, wind distributions, moisture distribution, and SST distribution in the analyses, we will have better NWP skills in hurricane analyses including hurricane intensity and tracks. Assimilating various observation data are supposed to play these roles in the analyses. To examine impacts of different types of observation data on NASA Goddard Earth Observing System (GEOS) model hurricane analyses and forecasts during the period of 2017 summer, this study performs data denial experiments using GEOS Atmospheric Data Assimilation System (ADAS), which is based on the hybrid 4D-EnVar GSI algorithm. Various types of observations such as microwave sounders, infrared sounders, TCvitals, and conventional data are removed in the experiments. In addition, the interaction between the different observation groups as certain instruments are removed from the analysis is investigated in detail using adjoint based forecast sensitivity observation impact (FSOI).

Hurricane↗
NASA NTRS2018

Examining Tropical Oceanic Convection Using IMERG and CYGNSS

The Cyclone Global Navigation Satellite System (CYGNSS) is a multi-satellite constellation that measures ocean wind speed using GPS reflectometry. CYGNSS wind measurements are not as impacted by rainfall, making them useful in and near tropical convective systems. Combining IMERG with CYGNSS enables the study of wind-precipitation interactions in convection, and shipborne radar can provide context for these analyses.

CYGNSS↗
NASA NTRS2018

Assimilation of GMI and ATMS Observations in the Rainbands of Hurricanes

We propose a novel Bayesian Monte Carlo Integration (BMCI) technique to retrieve the profiles of temperature, water vapor, and cloud liquid/ice water content from microwave cloudy measurements in the presence of tropical cyclones (TC). These retrievals then can either be directly used by meteorologists to analyze the structure of TCs or be assimilated into numerical models to provide accurate initial conditions for the NWP models. The BMCI technique is applied to the data from the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) and Global Precipitation Measurement (GPM) Microwave Imager (GMI). The retrieved profiles are then assimilated into Hurricane WRF using GSI data assimilation system. This talk presents the development of the BMCI retrieval system as well as the preliminary results of assimilating the retrievals into NASA GEOS-5 model.

Moradi, Isaac↗
NASA NTRS2018

The Roles of Climate Change and Climate Variability in the 2017 Atlantic Hurricane Season

The 2017 Atlantic hurricane season was extremely active with six major hurricanes, the third most on record. The sea-surface temperatures (SSTs) over the eastern Main Development Region (EMDR), where many tropical cyclones (TCs) developed during active months of August/September, were ~0.96 C above the 1901-2017 average (warmest on record): about ~0.42 C from a long-term upward trend and the rest (~80%) attributed to the Atlantic Meridional Mode (AMM). The contribution to the SST from the North Atlantic Oscillation (NAO) over the EMDR was a weak warming, while that from El Niño-Southern Oscillation (ENSO) was negligible. Nevertheless, ENSO, the NAO, and the AMM all contributed to favorable wind shear conditions, while the AMM also produced enhanced atmospheric instability. Compared with the strong hurricane years of 2005/2010, the ocean heat content (OHC) during 2017 was larger across the tropics, with higher SST anomalies over the EMDR and Caribbean Sea. On the other hand, the dynamical/thermodynamical atmospheric conditions, while favorable for enhanced TC activity, were less prominent than in 2005/2010 across the tropics. The results suggest that unusually warm SST in the EMDR together with the long fetch of the resulting storms in the presence of record-breaking OHC may be key factors in driving the strong TC activity in 2017.

SST↗
NASA NTRS2018

Analysis and Applications of Water Vapor-Derived Multispectral Composites for Geostationary Satellites

Analysis of multispectral (red-green-blue, RGB) satellite image composites can be used to improve understanding of thermodynamic and / or dynamic features associated with the development of significant weather events (cyclones, hurricanes, intense convection, turbulence, etc.). These composites minimize the need for a more time consuming analysis of multiple images and can provide additional insight not available from a single channel. The enhanced water vapor imaging capabilities of the Advanced Baseline Imager on GOES-16,-17 satellites provide a unique opportunity to demonstrate this capability through a comparison of the Air Mass and Differential Water Vapor RGB image products for several case studies.

Jedlovec, Gary J.↗
NASA NTRS2018

Lightning Enriched Global Precipitation Feature Database

The Tropical Rainfall Measurement Mission (TRMM) has provided a wealth of insight about lightning and precipitation in the tropics. However TRMM did not provide coverage outside the tropics and sub-tropics (i.e., beyond ±38°latitude), and hence it was unable to sample the lightning activity and precipitation features over a large fraction of mid-latitude continents and oceans, including extratropical cyclone storm tracks. The Global Precipitation Measurement (GPM) mission picks up where TRMM left off in that it provides information on precipitation features in the mid-and high latitudes (up to 65°N/S). However, GPM lacks a lightning instrument that can provide additional insights into mid-latitude thunderstorm activity and distribution. Hence we integrate observations from coincident the ISS Lightning Imaging Sensor (LIS) and the World Wide Lightning Location Network (WWLLN) observations with measurements from the GPM constellation of satellites, in particular to extend the existing GPM Precipitation Feature (PF) database so its data parameters are similar to that of the TRMM PF database (i.e., precipitation + lighting). Currently, WWLLN and ISS-LIS lightning have been collocated into precipitation features defined from GPM core satellite and constellation satellites observations.

Precipitation↗
NASA NTRS2019

Comparing Flood-Producing Catastrophic Hurricanes in GEOS: A Study of Juan 1985 and Harvey 2017

Hurricanes Juan (1985) and Harvey (2017) bear remarkable similarities because of the exceptional amount of accumulated precipitation over coastal regions in the Gulf, consequent to the peculiar and rare situation in which a hurricane stalls for several days on a coastal area, displaying minimal progress. This is particularly dangerous because: a) terrestrial drag affect only part of the circulation so that weakening is not as fast as when there is rapid motion inland; b) a part of the circulation remains over water and as such low-level moisture flux convergence is maintained; c) precipitation lasts for a very long time over the same area; d) moisture recycling from flooded areas further contributes to maintaining flood conditions. From the forecast perspective, hurricanes with track singularities such as stalling points, loops, or multiple landfalls over the same region are exceptionally difficult to predict because they result from small variations of opposing mechanisms and are therefore intrinsically unstable. Intensity fluctuations and track singularities are strongly coupled. The representation of fluxes undergoing differential drag (ocean vs. land) inside the same circulation is critically dependent upon resolution. Recent modeling development efforts within the NASA Global Modeling and Assimilation Office (GMAO) have brought the horizontal resolution of the global cubed-sphere Goddard Earth Observing System (GEOS) atmospheric model down to 12 km. This has led to innovative findings in the field of tropical cyclone (TC) modeling within a global framework. The GEOS atmospheric model and data assimilation system (DAS), used to produce the MERRA-2 (Modern Era Retrospective analysis for Research and Applications) reanalysis, has a "Replay" capability that adds a forcing term to the model equations to constrain it to follow a specified trajectory. This capability is used to produce global, downscaled versions of the 50 km MERRA-2 reanalysis at a 12.5 km resolution. The full DAS and replay modes both use the Incremental Analysis Update or IAU for applying an analysis increment to the model's background state four times each day at 00Z, 06Z, 12Z and 18Z. In a full DAS mode, a six-hour free run of the model is made (Predictor Step), writing states that will be used as backgrounds or first-guesses for the analysis centered on 00Z. The Analysis system then produces its best estimate of the 00Z state by blending backgrounds with observations. The difference between this best estimate and the model's original first guess at 00Z is treated as an analysis increment and added uniformly as a forcing term to the model during a second, now forced, run of the 12Z to 03Z window, which produces the assimilated results. Replay mode is very similar, except only the 00Z background is needed from the predictor segment, which is thus half as long, and instead of doing an analysis, a previously analyzed state at 00Z is read in. The increment is then computed and applied to the corrector step in the same way as in the original DAS. When downscaling horizontal spatial filters can be applied to the "analysis" increment used to force the Corrector step, so as to reproduce the full meteorological state or selectively choose or discard certain forcings. In this presentation, full global hindcast simulations of Juan and operational forecasts of Harvey are compared.

Flooding↗