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NASA NTRS2002

Regional Climate Simulation and Data Assimilation with Variable-Resolution GCMs

Variable resolution GCMs using a global stretched grid (SG) with enhanced regional resolution over one or multiple areas of interest represents a viable new approach to regional climateklimate change and data assimilation studies and applications. The multiple areas of interest, at least one within each global quadrant, include the major global mountains and major global monsoonal circulations over North America, South America, India-China, and Australia. They also can include the polar domains, and the European and African regions. The SG-approach provides an efficient regional downscaling to mesoscales, and it is an ideal tool for representing consistent interactions of globaYlarge- and regionallmeso- scales while preserving the high quality of global circulation. Basically, the SG-GCM simulations are no different from those of the traditional uniform-grid GCM simulations besides using a variable-resolution grid. Several existing SG-GCMs developed by major centers and groups are briefly described. The major discussion is based on the GEOS (Goddard Earth Observing System) SG-GCM regional climate simulations.

Fox-Rabinovitz, Michael S.↗

NASA NTRS2006

The Australian National Airborne Field Experiment 2005: Soil Moisture Remote Sensing at 60 Meter Resolution and Up

Spatially-distributed soil moisture observations have applications spanning a wide range of spatial resolutions from the very local needs of individual farmers to the progressively larger areas of interest to weather forecasters, water resource managers, and global climate modelers. To date, the most promising approach for space-based remote sensing of soil moisture makes use of passive microwave emission radiometers at L-band frequencies (1-2 GHz). Several soil moisture-sensing satellites have been proposed in recent years, with the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission scheduled to be launched first in a couple years. While such a microwave-based approach has the advantage of essentially allweather operation, satellite size limits spatial resolution to 10's of km. Whether used at this native resolution or in conjunction with some type of downscaling technique to generate soil moisture estimates on a finer-scale grid, the effects of subpixel spatial variability play a critical role. The soil moisture variability is typically affected by factors such as vegetation, topography, surface roughness, and soil texture. Understanding and these factors is the key to achieving accurate soil moisture retrievals at any scale. Indeed, the ability to compensate for these factors ultimately limits the achievable spatial resolution and/or accuracy of the retrieval. Over the last 20 years, a series of airborne campaigns in the USA have supported the development of algorithms for spaceborne soil moisture retrieval. The most important observations involved imagery from passive microwave radiometers. The early campaigns proved that the retrieval worked for larger and larger footprints, up to satellite-scale footprints. These provided the solid basis for proposing the satellite missions. More recent campaigns have explored other aspects such as retrieval performance through greater amounts of vegetation. All of these campaigns featured extensive ground truth collection over a range of grid spacings, to provide a basis for examining the effects of subpixel variability. However, the native footprint size of the airborne L-band radiometers was always a few hundred meters. During the recently completed (November, 2005) National Airborne Field Experiment (NAFE) campaign in Australia, a compact L-band radiometer was deployed on a small aircraft. This new combination permitted routine observations at native resolutions as high as 60 meters, substantially finer than in previous airborne soil moisture campaigns, as well as satellite footprint areal coverage. The radiometer, the Polarimetric L-band Microwave Radiometer (PLMR) performed extremely well and operations included extensive calibration-related observations. Thus, along with the extensive fine-scale ground truth, the NAFE dataset includes all the ingredients for the first scaling studies involving very-high-native resolution soil moisture observations and the effects of vegetation, roughness, etc. A brief overview of the NAFE will be presented, then examples of the airborne observations with resolutions from 60 m to 1 km will be shown, and early results from scaling studies will be discussed.

Kim, E. J.↗

NASA NTRS2007

A New Paradigm for Assessing the Role of Agriculture in the Climate System and in Climate Change

This paper discusses the diverse climate forcings that impact agricultural systems, and contrasts the current paradigm of using global models downscaled to agricultural areas (a top-down approach) with a new paradigm that first assesses the vulnerability of agricultural activities to the spectrum of environmental risk including climate (a bottom-up approach). To illustrate the wide spectrum of climate forcings, regional climate forcings are presented including land-use/land-cover change and the influence of aerosols on radiative and biogeochemical fluxes and cloud/precipitation processes, as well as how these effects can be teleconnected globally. Examples are presented of the vulnerability perspective, along with a small survey of the perceived drought impacts in a local area, in which a wide range of impacts for the same precipitation deficits are found. This example illustrates why agricultural assessments of risk to climate change and variability and of other environmental risks should start with a bottom-up perspective.

Pielke, Roger A., Sr.↗

NASA NTRS2008

Towards Verification of Unstructured-Grid Solvers

New methodology for verification of computational methods using unstructured grids is presented. The discretization order properties are studied in computational windows, easily constructed within a collection of grids or a single grid. The windows can be adjusted to isolate the interior discretization, the boundary discretization, or singularities. A major component of the methodology is the downscaling test, introduced previously for studying the convergence rates of truncation and discretization errors of finite-volume discretization schemes on general unstructured grids. Demonstrations of the method are shown, including a comparative accuracy assessment of commonly-used schemes on general mixed grids and the identification of local accuracy deterioration at intersections of tangency and inflow/outflow boundaries. Recommendations for the use of the methodology in large-scale computational simulations are given.

Thomas, James L.↗

NASA NTRS2006

Observed Scaling Behavior of Snow and Soil Moisture Signatures from the CLPX and NAFE Campaigns

Seasonal snow and soil moisture (SM) are important elements of the Earth's water cycle, acting as storage elements and by modulating water and energy exchanges between the land surface and the atmosphere and space. Accurate estimates of snow water equivalent (SWE) and SM also play an important role in weather and climate models over a range of scales. There are many advantages for the retrieval of snow parameters using passive microwave sensors. However, the current scale mismatch between many high-resolution applications and available satellite snow sensor footprints (approx.25km) presents challenges. There is also a scale mismatch for planned L-band soil moisture satellite measurements with their large (50-100 km) passive microwave footprints. Combined radiometer-radar schemes are being explored as possible aids, but this is still an area of ongoing research. Retrieval accuracies are limited in part by complex, and potentially nonlinear relationships between SWE or SM and microwave emission signatures. We will use airborne and satellite observations from two field campaigns to examine the scaling behavior of brightness temperatures and SWE and SM across scales from 100 meters to 10's of kilometers. The results will provide examples of the appropriate spatial sampling scales for new sensors, and guidance for downscaling schemes. The two campaigns are NASA's Cold Land Processes Experiment- 1 (CLPX- 1 : Colorado, 2002 & 2003), and the Australian National Airborne Field Experiment (NAFE, Nov, 2005). The analyses will also illustrate the roles and spatial scales of the underlying phenomena (e.g., vegetation, topography) that control subpixel heterogeneity.

Kim, Edward J.↗

NASA NTRS2008

Towards Verification of Unstructured-Grid Solvers

New methodology for verification of finite-volume computational methods using unstructured grids is presented. The discretization order properties are studied in computational windows, easily constructed within a collection of grids or a single grid. Tests are performed within each window and address a combination of problem-, solution-, and discretization/grid-related features affecting discretization error convergence. The windows can be adjusted to isolate particular elements of the computational scheme, such as the interior discretization, the boundary discretization, or singularities. Studies can use traditional grid-refinement computations within a fixed window or downscaling, a recently-introduced technique in which computations are made within windows contracting toward a focal point of interest. Grids within the windows are constrained to be consistently refined, allowing a meaningful assessment of asymptotic error convergence on unstructured grids. Demonstrations of the method are shown, including a comparative accuracy assessment of commonly-used schemes on general mixed grids and the identification of local accuracy deterioration at boundary intersections. Recommendations to enable attainment of design-order discretization errors for large-scale computational simulations are given.

Thomas, James L.↗

NASA NTRS2008

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model

The NASA Gravity Recovery and Climate Experiment (GRACE) system of satellites provides observations of large-scale, monthly terrestrial water storage (TWS) changes. In. this presentation we describe a land data assimilation system that ingests GRACE observations and show that the assimilation improves estimates of water storage and fluxes, as evaluated against independent measurements. The ensemble-based land data assimilation system uses a Kalman smoother approach along with the NASA Catchment Land Surface Model (CLSM). We assimilated GRACE-derived TWS anomalies for each of the four major sub-basins of the Mississippi into the Catchment Land Surface Model (CLSM). Compared with the open-loop (no assimilation) CLSM simulation, assimilation estimates of groundwater variability exhibited enhanced skill with respect to measured groundwater. Assimilation also significantly increased the correlation between simulated TWS and gauged river flow for all four sub-basins and for the Mississippi River basin itself. In addition, model performance was evaluated for watersheds smaller than the scale of GRACE observations, in the majority of cases, GRACE assimilation led to increased correlation between TWS estimates and gauged river flow, indicating that data assimilation has considerable potential to downscale GRACE data for hydrological applications. We will also describe how the output from the GRACE land data assimilation system is now being prepared for use in the North American Drought Monitor.

Reichle, Rolf H.↗

NASA NTRS2011

Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation

Passive microwave (e.g. AMSR-E) and visible spectrum (e.g. MODIS) measurements of snow states have been used in conjunction with land surface models to better characterize snow pack states, most notably snow water equivalent (SWE). However, both types of measurements have limitations. AMSR-E, for example, suffers a loss of information in deep/wet snow packs. Similarly, MODIS suffers a loss of temporal correlation information beyond the initial accumulation and final ablation phases of the snow season. Gravimetric measurements, on the other hand, do not suffer from these limitations. In this study, gravimetric measurements from the Gravity Recovery and Climate Experiment (GRACE) mission are used in a land surface model data assimilation (DA) framework to better characterize SWE in the Mackenzie River basin located in northern Canada. Comparisons are made against independent, ground-based SWE observations, state-of-the-art modeled SWE estimates, and independent, ground-based river discharge observations. Preliminary results suggest improved SWE estimates, including improved timing of the subsequent ablation and runoff of the snow pack. Additionally, use of the DA procedure can add vertical and horizontal resolution to the coarse-scale GRACE measurements as well as effectively downscale the measurements in time. Such findings offer the potential for better understanding of the hydrologic cycle in snow-dominated basins located in remote regions of the globe where ground-based observation collection if difficult, if not impossible. This information could ultimately lead to improved freshwater resource management in communities dependent on snow melt as well as a reduction in the uncertainty of river discharge into the Arctic Ocean.

Forman, Bart↗

NASA NTRS2011

Next-Generation Satellite Precipitation Products for Understanding Global and Regional Water Variability

A major challenge in understanding the space-time variability of continental water fluxes is the lack of accurate precipitation estimates over complex terrains. While satellite precipitation observations can be used to complement ground-based data to obtain improved estimates, space-based and ground-based estimates come with their own sets of uncertainties, which must be understood and characterized. Quantitative estimation of uncertainties in these products also provides a necessary foundation for merging satellite and ground-based precipitation measurements within a rigorous statistical framework. Global Precipitation Measurement (GPM) is an international satellite mission that will provide next-generation global precipitation data products for research and applications. It consists of a constellation of microwave sensors provided by NASA, JAXA, CNES, ISRO, EUMETSAT, DOD, NOAA, NPP, and JPSS. At the heart of the mission is the GPM Core Observatory provided by NASA and JAXA to be launched in 2013. The GPM Core, which will carry the first space-borne dual-frequency radar and a state-of-the-art multi-frequency radiometer, is designed to set new reference standards for precipitation measurements from space, which can then be used to unify and refine precipitation retrievals from all constellation sensors. The next-generation constellation-based satellite precipitation estimates will be characterized by intercalibrated radiometric measurements and physical-based retrievals using a common observation-derived hydrometeor database. For pre-launch algorithm development and post-launch product evaluation, NASA supports an extensive ground validation (GV) program in cooperation with domestic and international partners to improve (1) physics of remote-sensing algorithms through a series of focused field campaigns, (2) characterization of uncertainties in satellite and ground-based precipitation products over selected GV testbeds, and (3) modeling of atmospheric processes and land surface hydrology through simulation, downscaling, and data assimilation. An overview of the GPM mission, science status, and synergies with HyMex activities will be presented

Hou, Arthur Y.↗

NASA NTRS2011

Using Enhanced Grace Water Storage Data to Improve Drought Detection by the U.S. and North American Drought Monitors

NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations of the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including groundwater. The U.S. and North American Drought Monitors rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors by filling this observational gap. GRACE TWS data were assimilating into the Catchment Land Surface Model using an ensemble Kalman smoother enabling spatial and temporal downscaling and vertical decomposition into soil moisture and groundwater components. The Drought Monitors combine several short- and long-term drought indicators expressed in percentiles as a reference to their historical frequency of occurrence. To be consistent, we generated a climatology of estimated soil moisture and ground water based on a 60-year Catchment model simulation, which was used to convert seven years of GRACE assimilated fields into drought indicator percentiles. At this stage we provide a preliminary evaluation of the GRACE assimilated moisture and indicator fields.

Houborg, Rasmus↗

NASA NTRS2011

Climate Change Impacts on North Dakota: Agriculture and Hydrology

North Dakota is one of the principal producers of agricultural commodities in the USA, including over half of the total spring wheat production. While the region includes some of the best agricultural lands in the world, the steep temperature and precipitation gradients also make it one of the most sensitive to climate change. Over the 20th century, both the temperature and the pattern of precipitation in the state have changed; one of the most dramatic examples of the consequences of this change is the Devils Lake flooding. In two studies, we estimated the climate change impacts on crop yields and on the hydrology of the Devils Lake basin. The projections of six GCMs, driven by three SRES scenarios were statistically downscaled for multiple locations throughout the state, for the 2020s, 2050s, and 2080s climate. Averaged over all GCMs, there is a small increase in precipitation, by 0.6 - 1.1% in 2020s, 3.1 - 3.5% in 2050s, and 3.0 - 7.6% in 2080s. This change in precipitation varies with the seasons, with cold seasons becoming wetter and warm seasons not changing.

FROM↗

NASA NTRS2011

Reconciling Satellite-Derived Atmospheric Properties with Fine-Resolution Land Imagery: Insights for Atmospheric Correction

This paper investigates to what extent satellite measurements of atmospheric properties can be reconciled with fine-resolution land imagery, in order to improve the estimates of surface reflectance through physically based atmospheric correction. The analysis deals with mountainous area (Landsat scene of Peruvian Amazon/Andes, 72 E and 13 S), where the atmosphere is highly variable. Data from satellite sensors were used for characterization of the key atmospheric constituents: total water vapor (TWV), aerosol optical depth (AOD), and total ozone. Constituent time series revealed the season-dependent mean state of the atmosphere and its variability. Discrepancies between AOD from the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS) highlighted substantial uncertainty of atmospheric aerosol properties. The distribution of TWV and AOD over a Landsat scene was found to be exponentially related to ground elevation (mean R(sup 2) of 0.82 and 0.29, respectively). In consequence, the atmosphere-induced and seasonally varying bias of the top-of-atmosphere signal was also elevation dependent (e.g., mean Normalized Difference Vegetation Index bias at 500 m was 0.06 and at 4000 m was 0.01). We demonstrate that satellite measurements of key atmospheric constituents can be downscaled and gap filled with the proposed "background + anomalies" approach, to allow for a better compatibility with fine-resolution land surface imagery. Older images (i.e., predating the MODIS/ATSR era), without coincident atmospheric data, can be corrected using climatologies derived from time series of satellite retrievals. Averaging such climatologies over space compromises the quality of correction result to a much greater degree than averaging them over time. We conclude that the quality of both recent and older fine-resolution land surface imagery can be improved with satellite-based atmospheric data acquired to date.

Zelazowski, Przemyslaw↗

NASA NTRS2012

Propagation of Convective Complexes Observed by TRMM in the Eastern Tropical Atlantic

Precipitation maxima during the West African summer monsoon propagate generally westward in tandem with African easterly waves. A heretofore unreported, repeating pattern of northward drift of precipitation maxima is detected on Tropical Rainfall Measurement Mission (TRMM satellite) time-latitude distributions of daily accumulations over the eastern tropical Atlantic. Corresponding 3-hourly TRMM accumulations show that the northward drifting envelopes of precipitation during August 2006 are often comprised of individual swaths propagating towards the southwest, presumably as mesoscale squall lines. The implied northward drift on the time-latitude distribution is a component of a resultant northwestward movement. The study examines the entire available record of TRMM precipitation observations, 1998-2010, to summarize TRMM maxima propagation over the eastern tropical Atlantic. Meridional displacements of precipitation maxima are most prevalent in June-September 2006, occurring less frequently during other summers. An investigation of geopotential and circulation fields, limited to two case studies, suggests mechanisms to explain some of the observed propagation of TRMM maxima. In one event, northward drift of the precipitation envelope is consistent with the corresponding displacement of the intertropical convergence zone trough, although the southwest propagation of individual mesoscale convection maxima does not correspond to any synoptic feature on reanalysis circulation or reanalysis downscaled by a regional model. One speculation is that southwestward propagation of precipitation maxima could be caused by regeneration of convection at outflow boundaries of mature thunderstorms.

Druyan, Leonard M.↗

NASA NTRS2010

Modelling the Future Hydroclimatology of the Lower Fraser River and its Impacts on the Spawning Migration Survival of Sockeye Salmon

Short episodic high temperature events can be lethal for migrating adult Pacific salmon (Oncorhynchus spp.). We downscaled temperatures for the Fraser River, British Columbia to evaluate the impact of climate warming on the frequency of exceeding thermal thresholds associated with salmon migratory success. Alarmingly, a modest 1.0 C increase in average summer water temperature over 100 years (1981-2000 to 2081-2100) tripled the number of days per year exceeding critical salmonid thermal thresholds (i.e. 19.0 C). Refined thresholds for two populations (Gates Creek and Weaver Creek) of sockeye salmon (Oncorhynchus nerka) were defined using physiological constraint models based on aerobic scope. While extreme temperatures leading to complete aerobic collapse remained unlikely under our warming scenario, both populations were increasingly forced to migrate upriver at reduced levels of aerobic performance (e.g. in 80% of future simulations, => 90% of salmon encountered temperatures exceeding population specific thermal optima for maximum aerobic scope; T(sub opt)) = 16.3 C for Gates Creek and T(sub sopt)=14.5 C for Weaver Creek). Assuming recent changes to river entry timing persist, we also predicted dramatic increases in the probability of freshwater mortality for Weaver Creek salmon due to reductions in aerobic, and general physiological, performance (e.g. in 42% of future simulations =>50% of Weaver Creek fish exceeded temperature thresholds associated with 0 - 60% of maximum aerobic scope). Potential for adaptation via directional selection on run-timing was more evident for the Weaver Creek population. Early entry Weaver Creek fish experienced 25% (range: 15 - 31%) more suboptimal temperatures than late entrants, compared with an 8% difference (range: 0 - 17%) between early and late Gates Creek fish. Our results emphasize the need to consider daily temperature variability in association with population-specific differences in behaviour and physiological constraints when forecasting impacts of climate change on migratory survival of aquatic species.

Hague, M. J.↗

NASA NTRS2012

Assessment of Data Assimilation with the Prototype High Resolution Rapid Refresh for Alaska (HRRRAK)

The Arctic Region Supercomputing Center has been running a quasi-operational prototype of a High Resolution Rapid Refresh for Alaska (HRRRAK) at 3km resolution, initialized by the 13km Rapid Refresh (RR). Although the RR assimilates a broad range of observations into its analyses, experiments with the HRRRAK suggest that there may be added value in assimilating observations into the 3km initial conditions, downscaled from the 13km RR analyses. The NASA Short-term Prediction Research and Transition (SPoRT) group has been using assimilated data from the Atmospheric Infrared Sounder (AIRS) in WRF and WRF-Var simulations since 2004 with promising results. The sounder is aboard NASA s Aqua satellite, and provides vertical profiles of temperature and humidity. The Gridpoint Statistical Interpolation (GSI) system is then used to assimilate these vertical profiles into WRF forecasts. In this work, we assess the use of AIRS data in combination with other global data assimilation products on non-assimilated HRRRAK case studies. Two separate weather events will be assessed to qualitatively and quantitatively assess the impacts of AIRS data on HRRRAK forecasts.

Harrison, Kayla↗

NASA NTRS2012

Assessment of Data Assimilation with the Prototype High Resolution Rapid Refresh for Alaska (HRRRAK)

Harrison, Kayla↗

NASA NTRS2012

Drought Indicators Based on Model Assimilated GRACE Terrestrial Water Storage Observations

The Gravity Recovery and Climate Experiment (GRACE) twin satellites observe time variations in Earth's gravity field which yield valuable information about changes in terrestrial water storage (TWS). GRACE is characterized by low spatial (greater than 150,000 square kilometers) and temporal (greater than 10 day) resolution but has the unique ability to sense water stored at all levels (including groundwater) systematically and continuously. The GRACE Data Assimilation System (GRACE-DAS), based on the Catchment Land Surface Model (CLSM) enhances the value of the GRACE water storage data by enabling spatial and temporal downscaling and vertical decomposition into moisture 39 components (i.e. groundwater, soil moisture, snow), which individually are more useful for scientific applications. In this study, GRACE-DAS was applied to North America and GRACE-based drought indicators were developed as part of a larger effort that investigates the possibility of more comprehensive and objective identification of drought conditions by integrating spatially, temporally and vertically disaggregated GRACE data into the U.S. and North American Drought Monitors. Previously, the Drought Monitors lacked objective information on deep soil moisture and groundwater conditions, which are useful indicators of drought. Extensive datasets of groundwater storage from USGS monitoring wells and soil moisture from the Soil Climate Analysis Network (SCAN) were used to assess improvements in the hydrological modeling skill resulting from the assimilation of GRACE TWS data. The results point toward modest, but statistically significant, improvements in the hydrological modeling skill across major parts of the United States, highlighting the potential value of GRACE assimilated water storage field for improving drought detection.

Houborg, Rasmus↗

NASA NTRS2014

Climate Scenarios for the NASA / USAID SERVIR Project: Challenges for Multiple Planning Horizons

SERVIR, an acronym meaning "to serve" in Spanish, is a joint venture between NASA and the U.S. Agency for International Development (USAID) which provides satellite-based Earth observation data, modeling, and science applications to help developing nations in Central America, East Africa and the Himalayas improve environmental decision making. Anticipating climate variability / climate change impacts has now become an important component of the SERVIR efforts to build capacity in these regions. Uncertainty in hydrometeorological components of climate variations and exposure to extreme events across scales from weather to climate are of particular concern. We report here on work to construct scenarios or outlooks that are being developed as input drivers for decision support systems (DSSs) in a variety of settings. These DSSs are being developed jointly by a broad array NASA Applied Science Team (AST) Investigations and user communities in the three SERVIR Hub Regions, Central America, East Africa and the Himalayas. Issues span hydrologic / water resources modeling, agricultural productivity, and forest carbon reserves. The scenarios needed for these efforts encompass seasonal forecasts, interannual outlooks, and likely decadal / multi-decadal trends. Providing these scenarios across the different AST efforts enables some level of integration in considering regional responses to climate events. We will discuss a number of challenges in developing this continuum of scenarios including the identification and "mining" of predictability, addressing multiple continental regions, issues of downscaling global model integrations to regional / local applications (i.e. hydrologic and crop modeling). We compare / contrast the role of the U.S. National Multi- Model Experiment initiative in seasonal forecasts and the CMIP-5 climate model experiments in supporting these efforts. Examples of these scenarios, their use, and an assessment of their utility as well as limitations will be presented.

Robertson, Franklin R.↗