Preliminary Test of ERTS-1 Imagery for Improving Definition of Natural Streamflow
Preliminary test of ERTS-1 imagery for improving definition of natural streamflow, using two basins in Chesapeake Bay area
Hollyday, E. F.↗
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Prediction of Hydrological Drought: What Can We Learn From Continental-Scale Offline Simulations?
Land surface model experiments are used to quantify, across the coterminous United States, the contributions (isolated and combined) of soil moisture and snowpack initialization to the skill of seasonal streamflow forecasts at multiple leads and for different start dates. Forecasted streamflows are compared to naturalized streamflow observations where available and to synthetic (model-generated) streamflow data elsewhere. We find that snow initialization has a major impact on skill in the mountainous western U.S. and in a portion of the northern Great Plains; a mid-winter (January 1) initialization of snow in these areas leads to significant skill in the spring melting season. Soil moisture initialization also contributes to skill, and although the maximum contributions are not as large as those seen for snow initialization, the soil moisture contributions extend across a much broader geographical area. Soil moisture initialization can contribute to skill at long leads (up to 5 or 6 months), particularly for forecasts issued during winter.
Koster, Randal↗
The Contribution of Soil Moisture Information to Forecast Skill: Two Studies
This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.
Koster, Randal↗
Predicting Hydrological Drought: Relative Contributions of Soil Moisture and Snow Information to Seasonal Streamflow Prediction Skill
in this study we examine how knowledge of mid-winter snow accumulation and soil moisture conditions contribute to our ability to predict streamflow months in advance. A first "synthetic truth" analysis focuses on a series of numerical experiments with multiple sophisticated land surface models driven with a dataset of observations-based meteorological forcing spanning multiple decades and covering the continental United States. Snowpack information by itself obviously contributes to the skill attained in streamflow prediction, particularly in the mountainous west. The isolated contribution of soil moisture information, however, is found to be large and significant in many areas, particularly in the west but also in region surrounding the Great Lakes. The results are supported by a supplemental, observations-based analysis using (naturalized) March-July streamflow measurements covering much of the western U.S. Additional forecast experiments using start dates that span the year indicate a strong seasonality in the skill contributions; soil moisture information, for example, contributes to kill at much longer leads for forecasts issued in winter than for those issued in summer.
Koster, R.↗
Using Historical Precipitation, Temperature, and Runoff Observations to Evaluate Evaporation Formulations in Land Surface Models
Key to translating soil moisture memory into subseasonal precipitation and air temperature forecast skill is a realistic treatment of evaporation in the forecast system used - in particular, a realistic treatment of how evaporation responds to variations in soil moisture. The inherent soil moisture-evaporation relationships used in today's land surface models (LSMs), however, arguably reflect little more than guesswork given the lack of evaporation and soil moisture data at the spatial scales represented by regional and global models. Here we present a new approach for evaluating this critical aspect of LSMs. Seasonally averaged precipitation is used as a proxy for seasonally-averaged soil moisture, and seasonally-averaged air temperature is used as a proxy for seasonally-averaged evaporation (e.g., more evaporative cooling leads to cooler temperatures)~ the relationship between historical precipitation and temperature measurements accordingly mimics in certain important ways nature's relationship between soil moisture and evaporation. Additional information on the relationship is gleaned from joint analysis of precipitation and streamflow measurements. An experimental framework that utilizes these ideas to guide the development of an improved soil moisture-evaporation relationship is described and demonstrated.
Koster, Randal D.↗
"Efficiency Space" - A Framework for Evaluating Joint Evaporation and Runoff Behavior
At the land surface, higher soil moisture levels generally lead to both increased evaporation for a given amount of incoming radiation (increased evaporation efficiency) and increased runoff for a given amount of precipitation (increased runoff efficiency). Evaporation efficiency and runoff efficiency can thus be said to vary with each other, motivating the development of a unique hydroclimatic analysis framework. Using a simple water balance model fitted, in different experiments, with a wide variety of functional forms for evaporation and runoff efficiency, we transform net radiation and precipitation fields into fields of streamflow that can be directly evaluated against observations. The optimal combination of the functional forms the combination that produces the most skillful stream-flow simulations provides an indication for how evaporation and runoff efficiencies vary with each other in nature, a relationship that can be said to define the overall character of land surface hydrological processes, at least to first order. The inferred optimal relationship is represented herein as a curve in efficiency space and should be valuable for the evaluation and development of GCM-based land surface models, which by this measure are often found to be suboptimal.
GCM↗
The Hurricane-Flood-Landslide Continuum
In August 2004, representatives from NOAA, NASA, the USGS, and other government agencies convened in San Juan, Puerto Rim for a workshop to discuss a proposed research project called the Hurricane-Flood-Landslide Continuum (HFLC). The essence of the HFLC is to develop and integrate tools across disciplines to enable the issuance of regional guidance products for floods and landslides associated with major tropical rain systems, with sufficient lead time that local emergency managers can protect vulnerable populations and infrastructure. All three lead agencies are independently developing precipitation-flood-debris flow forecasting technologies, and all have a history of work on natural hazards both domestically and overseas. NOM has the capability to provide tracking and prediction of storm rainfall, trajectory and landfall and is developing flood probability and magnTtude capabilities. The USGS has the capability to evaluate the ambient stability of natural and man-made landforms, to assess landslide susceptibilities for those landforms, and to establish probabilities for initiation of landslides and debris flows. Additionally, the USGS has well-developed operational capacity for real-time monitoring and reporting of streamflow across distributed networks of automated gaging stations (http://water.usgs.gov/waterwatch/). NASA has the capability to provide sophisticated algorithms for satellite remote sensing of precipitation, land use, and in the future, soil moisture. The Workshop sought to initiate discussion among three agencies regarding their specific and highly complimentary capabilities. The fundamental goal of the Workshop was to establish a framework that will leverage the strengths of each agency. Once a prototype system is developed for example, in relatively data-rich Puerto Rim, it could be adapted for use in data-poor, low-infrastructure regions such as the Dominican Republic or Haiti. This paper provides an overview of the Workshop s goals, presentations and recommendations with respect to the development of the HFLC.
Negri, Andrew J.↗
The Simulation and Subseasonal Forecasting of Hydrological Variables: Insights from a Simple Water Balance Model
Past work has shown that a land surface model’s (LSM’s) implicit (not explicitly coded) relationships between soil moisture and both evapotranspiration (ET) and runoff largely determine the LSM’s hydrological behavior. Here we estimate the relationships that appear to be operating in the real world and compare them to those of the LSM component of a state-of-the-art Earth system model (ESM). The two sets of relationships are determined by calibrating them within a simple water balance model (WBM): once using stream gauge observations from small, unregulated rivers over the eastern half of the U.S., and once using the runoffs generated by the LSM as part of a state-of-the-art atmospheric reanalysis. Hydrological simulations and subseasonal hydrological forecasts performed with the two calibrated versions of the WBM provide two key results. First, the version calibrated to the LSM-generated runoffs does successfully reproduce, to first order, the hydrological behavior of the full LSM within its ESM environment. Second, of the two WBM versions, the one calibrated to the observations reproduces more accurately a broad collection of fully independent streamflow observations as well as a similarly broad collection of in-situ soil moisture measurements. Taken together, the two results suggest that the observations-calibrated ET and runoff efficiency functions do successfully represent, at least to some degree, soil moisture controls over hydrological variability in Nature and can serve as potentially useful targets for further LSM development.
Water Balance Model↗
The Pattern Across the Continental United States of Evapotranspiration Variability Associated with Water Availability
The spatial pattern across the continental United States of the interannual variance of warm season water-dependent evapotranspiration, a pattern of relevance to land-atmosphere feedback, cannot be measured directly. Alternative and indirect approaches to estimating the pattern, however, do exist, and given the uncertainty of each, we use several such approaches here. We first quantify the water dependent evapotranspiration variance pattern inherent in two derived evapotranspiration datasets available from the literature. We then search for the pattern in proxy geophysical variables (air temperature, stream flow, and NDVI) known to have strong ties to evapotranspiration. The variances inherent in all of the different (and mostly independent) data sources show some differences but are generally strongly consistent they all show a large variance signal down the center of the U.S., with lower variances toward the east and (for the most part) toward the west. The robustness of the pattern across the datasets suggests that it indeed represents the pattern operating in nature. Using Budykos hydroclimatic framework, we show that the pattern can largely be explained by the relative strength of water and energy controls on evapotranspiration across the continent.
Air Temperature↗
Assimilation of Remotely Sensed Leaf Area Index into the Noah-MP Land Surface Model: Impacts on Water and Carbon Fluxes and States over the Continental U.S.
Accurate representation of vegetation states is required for the modeling of terrestrial water-energy-carbon exchanges and the characterization of the impacts of natural and anthropogenic vegetation changes on the land surface. This study presents a comprehensive evaluation of the impact of assimilating remote sensing-based Leaf Area Index (LAI) retrievals over the Continental U.S. in the Noah-MP land surface model, during a time period of 2000 to 2017. The results demonstrate that the assimilation has a beneficial impact on the simulation of key water budget terms such as soil moisture, evapotranspiration, snow depth, terrestrial water storage and streamflow, when compared with a large suite of reference datasets. In addition, the assimilation of LAI is also found to improve the carbon fluxes of Gross Primary Production (GPP) and Net Ecosystem Exchange (NEE). Most prominent improvements in the water and carbon variables are observed over the agricultural areas of the U.S., where assimilation improves the representation of vegetation seasonality impacted by cropping schedules. The systematic, added improvements from assimilation in a configuration that employs high quality boundary conditions highlight the significant utility of LAI data assimilation in capturing the impacts of vegetation changes.
anthropogenic vegetation↗
Indicators of Climate Change Impacts on the Water Cycle and Water Management
Managing water is a top social and economic responsibility and is expected to become even more critical as climate change, in addition to other human activities, alters water availability and quality. Robust indicators reflecting the effects of climate change on the U.S. and global water cycles are needed in order to appropriately manage water resources. Here, we describe a suite of seventeen water cycle and management indicators, which are based on synthesis of available datasets. These indicators include: average and heavy precipitation, standardized precipitation index, annual, 7-day low and 3-day high streamflow volume, streamflow timing, snow cover, snow water equivalent, groundwater level, lake water temperature, stream water temperature, dissolved oxygen, salinity, Palmer Drought Severity Index, water withdrawals and water use. We also identify three indicators that could be included in the suite of water cycle and management indicators with some additional, directed work: snowfall, evapotranspiration and soil moisture. Our conceptual framework focuses on known water cycle changes in addition to potential effects on management, and addresses water quantity and quality, as well as water use and related interactions with freshwater ecosystems, societal impacts, and management. Water cycle indicators are organized into three categories: (1) hydrologic processes, (2) water quality processes, and (3) water quality and quantity impacts. Indicators described here are recommended to serve as critical references for periodic climate assessments. As such, these indicators support analyses of the effects of global change on the natural environment, agriculture, energy, and water resources, among other sectors. Additionally, we identify research gaps and needs that can be addressed to advance the development of future indicators.
Christa D Peters-Lidard↗
Hemispherically Asymmetric Volcanic Forcing of Tropical Hydroclimate During the Last Millennium
Volcanic aerosols exert the most important natural radiative forcing of the last millennium. State-of-the-art paleoclimate simulations of this interval are typically forced with diverse spatial patterns of volcanic forcing, leading to different responses in tropical hydroclimate. Recently, theoretical considerations relating the intertropical convergence zone (ITCZ) position to the demands of global energy balance have emerged in the literature, allowing for a connection to be made between the paleoclimate simulations and recent developments in the understanding of ITCZ dynamics. These energetic considerations aid in explaining the well-known historical, paleoclimatic, and modeling evidence that the ITCZ migrates away from the hemisphere that is energetically deficient in response to asymmetric forcing. Here we use two separate general circulation model (GCM) suites of experiments for the last millennium to relate the ITCZ position to asymmetries in prescribed volcanic sulfate aerosols in the stratosphere and related asymmetric radiative forcing. We discuss the ITCZ shift in the context of atmospheric energetics and discuss the ramifications of transient ITCZ migrations for other sensitive indicators of changes in the tropical hydrologic cycle, including global streamflow. For the first time, we also offer insight into the large-scale fingerprint of water isotopologues in precipitation (delta sup 18 Op) in response to asymmetries in radiative forcing. The ITCZ shifts away from the hemisphere with greater volcanic forcing. Since the isotopic composition of precipitation in the ITCZ is relatively depleted compared to areas outside this zone, this meridional precipitation migration results in a large-scale enrichment (depletion) in the isotopic composition of tropical precipitation in regions the ITCZ moves away from (toward). Our results highlight the need for careful consideration of the spatial structure of volcanic forcing for interpreting volcanic signals in proxy records and therefore in evaluating the skill of Common Era climate model output.
Radiative forcing↗