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At least 37 records · Page 2

Exploiting the Convergence of Evidence in Satellite Data for Advanced Weather Index Insurance Design

The goal of drought-related weather index insurance (WII) is to protect smallholder farmers against the risk of weather shocks and to increase their agricultural productivity. Estimates of precipitation and vegetation greenness are the two dominant satellite datasets. However, ignoring additional moisture- and energy-related processes that influence the response of vegetation to rainfall leads to an incomplete representation of the hydrologic cycle. This study evaluates the added value of considering multiple independent satellite-based variables to design, calibrate, and validate weather insurance indices on the African continent. The satellite data include two rainfall datasets, soil moisture, the evaporative stress index (ESI), and vegetation greenness. We limit artificial advantages by resampling all datasets to the same spatial (0.25°) and temporal (monthly) resolution, although datasets with a higher spatial resolution might have an added value, if considered as the single source of information for localized applications. A higher correlation coefficient between the moisture-focused variables and the normalized difference vegetation index (NDVI), an indicator for vegetation vigor, provides evidence for the datasets’ capability to capture agricultural drought conditions on the ground. The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall dataset, soil moisture, and ESI show higher correlations with the (lagged) NDVI in large parts of Africa, for different land covers and various climate zones, than the African Rainfall Climatology, version 2 (ARC2), rainfall dataset, which is often used in WII. A comparison to drought years as reported by farmers in Ethiopia, Senegal, and Zambia indicates a high “hit rate” of all satellite-derived anomalies regarding the detection of severe droughts but limitations regarding moderate drought events.

drought↗

Relating evaporative fraction to remotely sensed data at the FIFE site

Evaporative fractions at surface flux stations on the Konza Prairie are investigated by means of heat-flux estimation, evaporative fractions, and other remotely sensed parameters. Radiometric surface-temperature measurements are used to calculate sensible heat, and evaporative fraction is characterized by comparing systematic differences and consistencies at 21 stations. The evaporative fractions are related to soil and vegetation data collected concurrently with attention given to specific correlations. Little variation is found in the evaporative fraction during the day for the four periods studied, although the most significant change corresponded with the lowest values of soil moisture, leaf-area indices, and simple ratio. Uncertainties in air/surface temperature differences and in small wind speeds affect the reliability of estimates of the surface fluxes.

Gurney, R. J.↗

Timescales of Land Surface Evapotranspiration Response

Soil and vegetation exert strong control over the evapotranspiration rate, which couples the land surface water and energy balances. A method is presented to quantify the timescale of this surface control using daily general circulation model (GCM) simulation values of evapotranspiration and precipitation. By equating the time history of evaporation efficiency (ratio of actual to potential evapotranspiration) to the convolution of precipitation and a unit kernel (temporal weighting function), response functions are generated that can be used to characterize the timescales of evapotranspiration response for the land surface model (LSM) component of GCMS. The technique is applied to the output of two multiyear simulations of a GCM, one using a Surface-Vegetation-Atmosphere-Transfer (SVAT) scheme and the other a Bucket LSM. The derived response functions show that the Bucket LSM's response is significantly slower than that of the SVAT across the globe. The analysis also shows how the timescales of interception reservoir evaporation, bare soil evaporation, and vegetation transpiration differ within the SVAT LSM.

Scott, Russell↗

Satellite remote sensing of surface energy balance - Success, failures, and unresolved issues in FIFE

Utilizing single-view-angle visible and NIR satellite observations, it was possible to make the necessary radiometric corrections to produce reliable estimates of the simple ratio and the normalized difference vegetation index as inputs to surface evaporation models. Agreement was achieved between helicopter and satellite measures of surface reflectance to within +/-1 percent absolute for both the visible and the NIR bands. A theoretical calculation utilizing radiative transfer models indicates that this translates into a +/-10 percent error in the estimation in Fpar.

Hall, Forrest G.↗

African Easterly Jet: Structure and Maintenance

This article investigates the African Easterly Jet (AEJ), its structure and the forcings contributing to its maintenance, critically revisiting previous work which attributed the maintenance of the jet to soil moisture gradients over tropical Africa. A state-of-the-art global model in a high-end computer framework is used to produce a 3-member 73-year ensemble run forced by observed SST to represent the Control run. The AEJ as produced by the Control is compared with the representation of the AEJ in the European Center for Medium Range Forecast Reanalyses (ERA-40) and other observational data sets and found very realistic. Five Experiments are then performed, each represented by sets of 3-member 22 year long (1980-2001) ensemble runs. The goal of the Experiments is to investigate the role of meridional soil moisture gradients, different land surface properties and orography. Unlike previous studies, which have suppressed soil moisture gradients within a highly idealized framework (i.e., the so-called bucket model), terrestrial evaporation control is here achieved with a highly sophisticated landsurface treatment and with an extensively tested and complex methodology. The results show that the AEJ is suppressed by a combination of absence of meridional evaporation gradients over Africa and constant vegetation, even if the individual forcings taken separately do not lead to the AEJ disappearance, but only its modification. Moreover, the suppression of orography also leads to a different circulation in which there is no AEJ. This work suggests that it is not just soil moisture gradients, but a unique combination of geographical features present only in northern tropical Africa, which causes and maintains the jet.

Wu, Man-Li C.↗

Atmospheric humidity deficits tell us how soil moisture deficits down-regulate ecosystem evaporation

Knowing how actual evaporation is down-regulated from potential evaporation during periods with soil moisture deficits is one of the greatest challenges towards computing evaporation everywhere on a regular basis. We propose the hypothesis that vegetated landscapes transmit information on soil moisture deficits through its down-regulation of evaporation, which in turn affects the humidification and growth of the planetary boundary layer. To test this hypothesis, here, we examined how the evaporative fraction, defined as the ratio between actual and potential evaporation, corresponds with the soil moisture stress index, defined as the relative humidity with a power law dependence on vapor pressure deficit times a parameter, β. We tested the parameterized soil moisture stress index with direct eddy covariance measurements of actual evaporation and computations of potential evaporation based on meteorological conditions, averaged on monthly time steps. The analysis was conducted on a dataset obtained from 144 FLUXNET sites. These sites spanned much of the world's climates and biomes and contained over 5900 months of observations. Observations of the evaporative fraction fit the model of the soil moisture stress index best for semi-arid and arid ecosystems, and least for the humid and wet ecosystems. Consequently, a significant relationship between measurements of the evaporative fraction and soil moisture stress index held for about one-half of the population of sites. Under this condition, the median value of the parameter, β, was 1.41. To investigate the mechanism of this empirical soil moisture stress index, we diagnosed it with a coupled evaporation-planetary boundary layer model. The soil moisture stress index is strongly related to surface resistance, as defined by inverting Penman-Monteith equation. Consequently, this index provides an independent estimate of surface resistance based on easy to measure mean monthly weather conditions like relative humidity and temperature. Thereby, this soil moisture stress index has potential to be applied to weather, climate and biogeochemical models and the interpretation of satellite derived evaporation products, like the one provided by the ECOSTRESS mission.

54 ENVIRONMENTAL SCIENCES↗

Relationship of multispectral satellite data to land surface evaporation from the Australian continent

Based on NOAA-9 AVHRR and Nimbus-7 SMMR satellite data, satellite indices of vegetation from the Australian continent are calculated for the period of May 1986 to April 1987. Visible (VIS) and near infrared (NIR) reflectances and the normalized difference (ND) vegetation index are calculated from the AVHRR sensor. The microwave polarization difference (PD) is also calculated as the difference between the vertically and horizontally polarized brightness temperatures at 37 GHz. ND, PD, VIS, and NIR indices were plotted against rainfall and water balance estimates of evaporation. It is concluded that direct satellite monitoring of annual evaporation across the Australian continent using PD or VIS satellite indices of vegetation biomass appears possible for areas with evaporation less than 600 mm/y and that use of the ND relationship at continental scale may underpredict monthly evaporation of forests relative to agriculture.

Smith, R. C. G.↗

Remotely-Sensed Regional-Scale Evapotranspiration of a Semi-Arid Great Basin Desert and its Relationship to Geomorphology, Soils, and Vegetation

Landsat thematic mapper data are used to estimate instantaneous regional-scale surface water and energy fluxes in a semi-arid Great Basin desert of the western United States. Results suggest that it is possible to scale from point measurements of environmental state variables to regional estimates of water and energy exchange. This research characterizes the unifying thread in the classical climate-topography-soil-vegetation relation -the surface water and energy balance-through maps of the partitioning of energy throughout the landscape. The study was conducted in Goshute Valley of northeastern Nevada, which is characteristic of most faulted graben valleys of the Basin and Range Province of the western United States. The valley comprises a central playa and lake plain bordered by alluvial fans emanating from the surrounding mountains. The distribution of evapotranspiration (ET) is lowest in the middle reaches of the fans where the water table is deep and plants are small, resulting in low evaporation and transpiration. Highest ET occurs in the center of the valley, particularly in the playa, where limited to no vegetation occurs, but evaporation is relatively high because of a shallow water table and silty clay soil capable of large capillary movement. Intermediate values of ET are associated with large shrubs and is dominated by transpiration.

Laymon, C.↗

Remotely-Sensed Regional-Scale Evapotranspiration of a Semi-Arid Great Basin Desert and its Relationship to Geomorphology, Soils, and Vegetation

Landsat Thematic Mapper data is used to estimate instantaneous regional-scale surface water and energy fluxes in a semi-arid Great Basin desert of the western United States. Results suggest that it is possible to scale from point measurements of environmental state variables to regional estimates of water and energy exchange. This research characterizes the unifying thread in the classical climate-topography-soil-vegetation relation-the surface water and energy balance-through maps of the partitioning of energy throughout the landscape. The study was conducted in Goshute Valley of northeastern Nevada, which is characteristic of most faulted graben valleys of the Basin and Range Province of the western United States. The valley comprises a central playa and lake plain bordered by alluvial fans emanating from the surrounding mountains. The distribution of evapotranspiration (ET) is lowest in the middle reaches of the fans where the water table is deep and plants are small, resulting in low evaporation and transpiration. Highest ET occurs in the center of the valley, particularly in the playa, where limited to no vegetation occurs, but evaporation is relatively high because of a shallow water table and silty clay soil capable of large capillary movement. Intermediate values of ET are associated with large shrubs and is dominated by transpiration.

Laymon, C.↗

The use of remotely sensed surface temperature and a spectral vegetation index for evaluating heat fluxes over the Konza Prairie

The relationship between surface temperature T(s) and the normalized difference vegetation index (NDVI) is examined to determine whether it can be used to characterize latent heat fluxes (LEs). The regression of T(s) on NDVI is studied in the context of surface heat fluxes over the prairie with a limited data set for four flux-measurement sites. The 17 flux-measurement stations at the sites provided data that are consistently significant at the 99-percent confidence level for the regression of T(s) on NDVI. Variations in the regression slopes are found to correlate with variations in the ground heat flux but not with LE. Important components of the regression of T(s) on NDVI include fractional vegetation cover and surface-soil moisture conditions. The relationship is important for determining the relative contributions of the soil and vegetation components of an area's total evaporative flux.

Hope, A. S.↗

Causal relationships of vegetation productivity with root zone water availability and atmospheric dryness at the catchment scale

Abstract. This study explores the causal relationships between catchment water availability, vapor pressure deficit, and gross primary productivity (GPP) across 341 catchments in the contiguous US. Seasonal climatic, hydrological, and vegetation characteristics were represented using the Horton index, ecological aridity index, evaporative fraction index, and carbon uptake efficiency. Statistical methods, including circularity statistics, correlation analysis, and causality tests, were employed to determine the complex interactions between catchment wetness, atmospheric dryness, and vegetation carbon uptake. The results revealed a maximum lag of 2 months in the intra-annual variability of catchment water supply–productivity and atmospheric water demand–productivity relationships, with hysteresis patterns varying with the catchment's hydrological characteristics. In catchments not permanently under water-limited or energy-limited conditions, vegetation experiences hydrological stress during the peak growing period, coinciding with the highest gross primary productivity and carbon uptake efficiency being out of phase with the Horton index and in phase with the evaporative fraction index. Causality analysis highlights strong temporal continuity in GPP seasonal characteristics, with a cause–effect relationship between catchment water supply, atmospheric demand, and vegetation productivity spanning a maximum of 2 months. These findings underscore the need for a comprehensive functional framework that integrates catchment water supply, atmospheric demand, and vegetation productivity to enhance our understanding and predictive capabilities with regard to ecosystem responses to climate change.

54 ENVIRONMENTAL SCIENCES↗

Assimilation of Remotely Sensed Leaf Area Index Enhances the Estimation of Anthropogenic Irrigation Water Use

Representation of irrigation in Earth System Models has advanced over the past decade, yet large uncertainties persist in the effective simulation of irrigation practices, particularly over locations where the on-ground practices and climate impacts are less reliably known. Here we investigate the utility of assimilating remotely sensed vegetation data for improving irrigation water use and associated fluxes within a land surface model. We show that assimilating optical sensor-based leaf area index estimates significantly improves the simulation of irrigation water use when compared to the USGS ground reports. For heavily irrigated areas, assimilation improves the evaporative fluxes and gross primary production (GPP) simulations, with the median correlation increasing by 0.1–1.1 and 0.3–0.6, respectively, as compared to the reference datasets. Further, bias improvements in the range of 14–35 mm mo^(−1) and 10–82 g m^(-2)mo^(−1) are obtained in evaporative fluxes and GPP as a result of incorporating vegetation constraints, respectively. These results demonstrate that the use of remotely sensed vegetation data is an effective, observation-informed, globally applicable approach for simulating irrigation and characterizing its impacts on water and carbon states.

Earth System Models↗

Regional Impacts of Urbanization in the United States

We simulate the impact of impervious surface areas (ISA) on the U.S. local and regional climate. At a local scale, we find the urban area warmer than the surrounding vegetation in most cities, except in arid climate cities where urban temperature is cooler for much of the daytime. For all 9 regions studied, simulated results show that the growing season maximum surface temperature difference between urban and the dominant vegetation occurs around mid-day and is strongest in the northern regions. Regional temperature differences of 3.0 C, 3.4 C, and 3.9 C were simulated in the Northeast, Midwest, and Northwest, respectively. In these regions evaporative cooling, during the growing season, creates a stronger urban heat island (UHI). The UHI is less pronounced during winter when vegetation is dormant. Our results suggest that the ISA temperature is set by building material's characteristics and its departure from that of the surrounding vegetation is essentially driven by evaporative cooling. Except when rainfall is small, the highest surface runoff to precipitation ratios are simulated in most cities, especially when precipitation events occur as heavy downpours. In terms of photosynthesis, we provide a detailed distribution of maximum production in the U.S., a needed product for policy and urban planners.

Bounoua, Lahouari↗

Predictability of Malaria Transmission Intensity in the Mpumalanga Province, South Africa, Using Land Surface Climatology and Autoregressive Analysis

There has been increasing effort in recent years to employ satellite remotely sensed data to identify and map vector habitat and malaria transmission risk in data sparse environments. In the current investigation, available satellite and other land surface climatology data products are employed in short-term forecasting of infection rates in the Mpumalanga Province of South Africa, using a multivariate autoregressive approach. The climatology variables include precipitation, air temperature and other land surface states computed by the Off-line Land-Surface Global Assimilation System (OLGA) including soil moisture and surface evaporation. Satellite data products include the Normalized Difference Vegetation Index (NDVI) and other forcing data used in the Goddard Earth Observing System (GEOS-1) model. Predictions are compared to long- term monthly records of clinical and microscopic diagnoses. The approach addresses the high degree of short-term autocorrelation in the disease and weather time series. The resulting model is able to predict 11 of the 13 months that were classified as high risk during the validation period, indicating the utility of applying antecedent climatic variables to the prediction of malaria incidence for the Mpumalanga Province.

Grass, David↗

Wildfire Risk Support via Satellite-Derived Vegetation Health and Land Surface Model Soil Moisture

Land Surface Model (LSM) and evaporative demand products provide advanced lead time to wildfire conditions that complement traditional fire indices and represent short-term changes that add context to overall, long-term drought conditions. Established fire indices typically use weather indicators (i.e., precipitation, temperature) and estimated dead fuel moisture to indirectly obtain land surface and sub-surface characterization. The convergence of LSM shallow and deep-layer soil moisture output and satellite-derived vegetation health combine to provide a tool for stakeholders to examine trends in the state of land surface conditions that can help assess wildfire threat. Satellite remote sensing data can constrain near-real time vegetation characteristics within the LSM and/or provide a derived stress index in order to help characterize the wildfire risk. In addition, a percentile product of soil moisture is derived from a comparison of current LSM conditions to the historical record of the LSM in order to put the current conditions in perspective relative to the season and geographic region. The 2015 season as well as the 2018 Camp Fire Complex in California were examined in terms of the changes in LSM soil moisture and vegetation states. Satellite vegetation health consistently showed decreases a month prior to wildfire initiation. Additionally, maximum changes in total column soil moisture corresponded with the greatest concentration of fire locations. While soil moisture deficits occurred in the shallow layers across northern California in 2018, significant deficits at all sub-surface levels were seen ahead of the Camp Fire event. This presentation will demonstrate the complementary value of LSM output and satellite measured vegetation health to diagnose short-term deficits in sub-surface soil moisture and the rapid decline in vegetation health which precedes large wildfire events.

Wildfire↗

The impact of summer rainfall on the temperature gradient along the United States-Mexico border

The international border running through the Sonoran Desert in southern Arizona and northern Sonora is marked by a sharp discontinuity in albedo and grass cover. The observed differences in surface properties are a result of long-term, severe overgrazing of the Mexican lands. Recently, investigators have shown the Mexican side of the border to have higher surface and air temperatures when compared to adjacent areas in the United State. The differences in temperatures appear to be more associated with differential evapotranspiration rates than with albedo changes along the border. In this study, the impact of summer rainfall on the observed seasonal and daily gradient in maximum temperature is examined. On a seasonal time scale, the temperature gradient increases with higher moisture levels, probably due to a vegetative response on the United States' side of the border; at the daily level, the gradient in maximum temperature decreases after a rain event as evaporation rates equalize between the countries. The results suggest that temperature differences between vegetated and overgrazed landscapes in arid areas are highly dependent upon the amount of moisture available for evapotranspiration.

Balling, Robert C., Jr.↗

Role of Antecedent Soil Moisture and Vegetation Stress in Lightning-Initiated Wildfires

Lightning-caused wildfires are a small percentage of all wildfire events within the Conterminous U.S. (CONUS), but they account for over 56% of the acreage burned. The atmospheric conditions favoring wildfire and rapid growth are well understood: large dewpoint depressions, unstable planetary boundary layer, strong winds, etc. However, antecedent land surface conditions affecting dead and live fuel moisture is more difficult to quantify. This study examines over 20 years of antecedent land surface, vegetation stress, and wildfire characteristic data associated with nearly 77,000 lightning-initiated wildfires from the U.S. Forest Service Wildfire Database. We will invoke two in-house databases generated by the NASA Short-term Prediction Research and Transition (SPoRT) Center: an observations-driven, climatological run of the Noah land surface model within the NASA Land Information System (i.e., SPoRT-LIS) to depict soil moisture deficits / anomalies, and a satellite-constrained Evaporative Stress Index (ESI) product to denote areas of stressed vegetation. We will mine these datasets associated with lightning-caused (and null) events to determine important relationships, distributions, and delineators that correspond to elevated threat areas for lightning-initiated wildfires.

Wildfire↗

Estimation of effective hydrologic properties of soils from observations of vegetation density

A one-dimensional model of the annual water balance is reviewed. Improvements are made in the method of calculating the bare soil component of evaporation, and in the way surface retention is handled. A natural selection hypothesis, which specifies the equilibrium vegetation density for a given, water limited, climate soil system, is verified through comparisons with observed data. Comparison of CDF's of annual basin yield derived using these soil properties with observed CDF's provides verification of the soil-selection procedure. This method of parameterization of the land surface is useful with global circulation models, enabling them to account for both the nonlinearity in the relationship between soil moisture flux and soil moisture concentration, and the variability of soil properties from place to place over the Earth's surface.

Tellers, T. E.↗