Search NASA⌕ Search

SEARCH · Search NASA

Results for “climate patterns”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 793 records · Page 44

Climate Forcings in the Industrial Era

The forcings that drive long-term climate change are not known with an accuracy sufficient to define future climate change. Anthropogenic greenhouse gases (GHGs), which are well measured, cause a strong positive (warming) forcing. But other, poorly measured, anthropogenic forcings, especially changes of atmospheric aerosols, clouds, and land-use patterns, cause a negative forcing that tends to offset greenhouse warming. One consequence of this partial balance is-that the natural forcing due to solar irradiance changes may play a larger role in long-term climate change than inferred from comparison with GHGs alone. Current trends in GHG climate forcings are smaller than in popular "business as usual" or 1% per year CO2 growth scenarios. The summary implication is a paradigm change for long-term climate projections: uncertainties in climate forcings have supplanted global climate sensitivity as the predominant issue.

Hansen, James E.↗

The Response of the Ozone Layer Under Abrupt 4xCO2 in CMIP6

Previous studies indicate a possible role of stratospheric ozone chemistry feedbacks in the climate response to 4xCO2, either via a reduction in equilibrium climate sensitivity (ECS) (Nowack et al., 2015), or via changes in the tropospheric circulation (Chiodo and Polvani, 2017). However, these effects are subject to uncertainty. Part of the uncertainty may stem from the dependency of the feedback on the pattern of the ozone response, as the radiative efficiency of ozone largely depends on its vertical distribution (Lacis et al., 1990). Here, an analysis is presented of the ozone layer response to 4xCO2 in chemistry–climate models (CCMs) which participated to CMIP intercomparisons. In a previous study using CMIP5 models, it has been shown that under 4xCO2, ozone decreases in the tropical lower stratosphere, and increases over the high latitudes and throughout the upper stratosphere. It was also found that a substantial portion of the spread in the tropical column ozone is tied to inter-model spread in tropical upwelling, which is in turn partly tied to ECS (Chiodo et al., 2018). Here, we revisit this connection using4xCO2 data from CMIP6, thereby exploiting the larger number of CCMs than in CMIP5. In addition, we explore the linearity of the ozone response, by complementing the analysis with simulations using transient CO2 forcing (1pc/year). We show that the pattern of the ozone response in is similar to CMIP5. In some models (e.g. WACCM), we find larger ozone responses in CMIP6 than in CMIP5, partly because of the larger ECS and thus larger upwelling response in the tropical pipe. In this presentation, we will discuss the relationship between radiative forcing, transport and ozone, as well as further implications for CMIP6 models.

Ozone layer↗

Preindustrial Control Simulations With HadGEM3-GC3.1 for CMIP6

Preindustrial control simulations with the third Hadley Centre Global Environmental Model,run in the Global Coupled configuration 3.1 of the Met Office Unified Model (HadGEM3-GC3.1) are presentedat two resolutions. These are N216ORCA025, which has a horizontal resolution of 60 km in the atmosphereand 0.25° in the ocean, and N96ORCA1, which has a horizontal resolution of 130 km in the atmosphereand 1° in the ocean. The aim of this study is to document the climate variability in these simulations, makecomparisons against present-day observations (albeit under different forcing), and discuss differencesarising due to resolution. In terms of interannual variability in the leading modes of climate variability thetwo resolutions behave generally very similarly. Notable differences are in the westward extent of El Niñoand the pattern of Atlantic multidecadal variability, in which N216ORCA025 compares more favorably toobservations, and in the Antarctic Circumpolar Current, which is far too weak in N216ORCA025. In the NorthAtlantic region, N216ORCA025 has a stronger and deeper Atlantic Meridional Overturning Circulation, whichcompares well against observations, and reduced biases in temperature and salinity in the North Atlanticsubpolar gyre. These simulations are being provided to the sixth Coupled Model Intercomparison Project(CMIP6) and provide a baseline against which further forced experiments may be assessed.

54 ENVIRONMENTAL SCIENCES↗

Applying double cropping and interactive irrigation in the North China Plain using WRF4.5

Abstract. Irrigated cultivation exerts a significant influence on the local climate and the hydrological cycle. The North China Plain (NCP) is known for its intricate agricultural system, marked by expansive cropland, high productivity, compact rotation, a semi-arid climate, and intensive irrigation practices. As a result, there has been considerable attention on the potential impact of this intensive irrigated agriculture on the local climate. However, studying the irrigation impact in this region has been challenging due to the lack of an accurate simulation of crop phenology and irrigation practices within the climate model. By incorporating double cropping with interactive irrigation, our study extends the capabilities of the Weather Research Forecast (WRF) model, which has previously demonstrated commendable performance in simulating single-cropping scenarios. This allows for two-way feedback between irrigated crops and climate, further enabling the inclusion of irrigation feedback from both ground and vegetation perspectives. The improved crop modeling system shows significant enhancement in capturing vegetation and irrigation patterns, which is evidenced by its ability to identify crop stages, estimate field biomass, predict crop yield, and project monthly leaf area index. The improved simulation of large-scale irrigated crops in the NCP can further enhance our understanding of the intricate relationship between agricultural development and climate change.

54 ENVIRONMENTAL SCIENCES↗

Perennials in Flood-Prone Areas of Agricultural Landscapes: A Climate Adaptation Strategy

Wet conditions across the US Midwest have forced farmers to delay planting of corn into June 2019, leading to a four-year low in projected corn yields. This event is part of a broader pattern that extends further back in history and is expected to worsen in future (Naz et al. 2016), raising concerns about the future sustainability of the corn-based economy. In this commentary, we suggest that deep-rooted perennial biomass crops will have considerable advantages for farmers under future climate once markets for cellulosic biofuels mature. Beyond climate-resilient cropping systems, research is suggesting that plants tolerant of wet conditions could benefit wetland conservation efforts while producing sustainable biomass for energy (Avellan et al. 2017, Melts et al. 2019).

54 ENVIRONMENTAL SCIENCES↗

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbonfluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle,we must also be able to understand and model its effects on dryland vegetation. Dynamic Global VegetationModels (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduceseasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to bothtotal productivity and competitive interactions with other plants, errors in how process-based models representphenology hinder our ability to predict climate change impacts. This may be particularly problematic in drylandecosystems where many species have developed a complex phenology in response to seasonal variability in bothmoisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure ofexisting phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) andgross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized modelparameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, wemodified the model to include a semi-deciduous phenology type and added flexibility to the representation ofgrass phenology. While optimizing parameters reduced model bias, the largest gains in model performance wereassociated with the development of our new representation of phenology. This modified model was able to bettercapture seasonal patterns of both leaf area index (R2=0.75) and gross primary productivity (R2=0.84), thoughits ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new modelalso resulted in a more realistic outcome of modeled competition between grass and shrubs. These findingsdemonstrate the importance of improving how DGVMs represent phenology in order to accurately forecastclimate change impacts in dryland ecosystems.

Ecosystem model Phenology Parameter optimization E↗

Economic Valuation of Coccidioidomycosis (Valley Fever) Projections in the United States in Response to Climate Change

Coccidioidomycosis, or valley fever, is an infectious fungal disease currently endemic to the southwestern United States. Symptoms of valley fever range in severity from flu-like illness to severe morbidity and mortality. Warming temperatures and changes in precipitation patterns may cause the area of endemicity to expand northward throughout the western United States, putting more people at risk for contracting valley fever. This may increase the health and economic burdens from this disease. We developed an approach to describe the relationship between climate conditions and valley fever incidence using historical data and generated projections of future incidence in response to both climate change and population trends using the Climate Change Impacts and Risk Analysis (CIRA) framework developed by the U.S. Environmental Protection Agency. We also developed a method to estimate economic impacts of valley fever that is based on case counts. For our 2000–15 baseline time period, we estimated annual medical costs, lost income, and economic welfare losses for valley fever in the United States were 400,000 USD per case, and the annual average total cost was 3.9 billion USD per year. For a high greenhouse gas emission scenario and accounting for population growth, we found that total annual costs for valley fever may increase up to 164% by year 2050 and up to 380% by 2090. By the end of the twenty-first century, valley fever may cost 620,000 USD per case and the annual average total cost may reach $18.5 billion per year. This work contributes to the broader effort to monetize climate change–attributable damages in the United States.

54 ENVIRONMENTAL SCIENCES↗

A multi-level load shape clustering and disaggregation approach to characterize patterns of energy consumption behavior

This study presents representative electrical load shapes, disaggregated to the end-use level, for over 5000 customer clusters across California’s residential, commercial, industrial and agricultural sectors. We developed a novel, multi-level load shape clustering approach for residential and commercial sectors leveraging interval meter data for over 350,000 California utility customers collected as a part of the Phase 4 California Demand Response (DR) Potential Study. The clustering approach allowed us to identify typical consumption patterns and categorize customers based on their daily load shape displayed throughout the year. For example, we were able to identify customers with particular energy technologies such as electric vehicles and rooftop solar, as well as building occupancy types such as restaurants, grocery stores and even unoccupied buildings, based solely on whole-building interval data. We then combined the load shape-based clusters with other customer information including building type, climate, geographical area, total consumption and low-income status, to create a set of customer clusters based on both demographics and usage patterns. Total cluster electricity demand was then disaggregated into a wide variety of end-uses using weather normalization and other publicly available end-use load shape datasets. The resulting disaggregated cluster load shapes will be released in anonymized form as part of the Phase 4 DR Potential Study. They will have wide-ranging applications in energy research and policy analysis, including estimation of energy efficiency (EE) and DR potential on the end-use level, time-dependent valuation of EE savings, building stock modeling, and developing customer targeting strategies for EE and DR programs.

Murthy, Samanvitha↗

Impacts of the Convective Transport Algorithm on Atmospheric Composition and Ozone-Climate Feedbacks in GEOS-CCM

Convective transport is one of the dominant factors in determining the composition of the troposphere. It is the main mechanism for lofting constituents from near-surface source regions to the middle and upper troposphere, where they can subsequently be advected over large distances. Gases reaching the upper troposphere can also be injected through the tropopause and play a subsequent role in the lower stratospheric ozone balance. Convection codes in climate models remain a great source of uncertainty for both the energy balance of the general circulation and the transport of constituents. This study uses the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) to perform a controlled experiment that isolates the impact of convective transport of constituents from the direct changes on the atmospheric energy balance. Two multi-year simulations are conducted. In the first, the thermodynamic variable, moisture, and all trace gases are transported using the multi-plume Relaxed-Arakawa-Schubert (RAS) convective parameterization. In the second simulation, RAS impacts the thermodynamic energy and moisture in this standard manner, but all other constituents are transported differently. The accumulated convective mass fluxes (including entrainment and detrainment) computed at each time step of the GCM are used with a diffusive (bulk) algorithm for the vertical transport, which above all is less efficient at transporting constituents from the lower to the upper troposphere. Initial results show the expected differences in vertical structure of trace gases such as carbon monoxide, but also show differences in lower stratospheric ozone, in a region where it can potentially impact the climate state of the model. This work will investigate in more detail the impact of convective transport changes by comparing the two simulations over many years (1996-2010), focusing on comparisons with observed constituent distributions and similarities and differences of patterns of inter-annual variability caused by the convective transport algorithm. In particular, the impact on lower stratospheric composition will be isolated and the subsequent feedbacks of ozone on the climate forcing and tropopause structure will be assessed.

Pawson, S.↗

Robust Anthropogenic Signal Identified in the Seasonal Cycle of Tropospheric Temperature

Previous work identified an anthropogenic fingerprint pattern in T AC (x, t), the amplitude of the seasonal cycle of mid- to upper-tropospheric temperature (TMT), but did not explicitly consider whether fingerprint identification in satellite T AC (x, t) data could have been influenced by real-world multidecadal internal variability (MIV). Here we address this question here using large ensembles (LEs) performed with five climate models. LEs provide many different sequences of internal variability noise superimposed on an underlying forced signal. Despite differences in historical external forcings, climate sensitivity, and MIV properties of the five models, their T AC (x, t) fingerprints are similar and statistically identifiable in 239 of the 240 LE realizations of historical climate change. Comparing simulated and observed variability spectra reveals that consistent fingerprint identification is unlikely to be biased by model underestimates of observed MIV. Even in the presence of large (factor of 3–4) intermodel and inter-realization differences in the amplitude of MIV, the anthropogenic fingerprints of seasonal cycle changes are robustly identifiable in models and satellite data. This is primarily due to the fact that the distinctive, global-scale fingerprint patterns are spatially dissimilar to the smaller-scale patterns of internal T AC (x, t) variability associated with the Atlantic multidecadal oscillation and El Niño–Southern Oscillation. The robustness of the seasonal cycle detection and attribution results shown here, taken together with the evidence from idealized aquaplanet simulations, suggest that basic physical processes are dictating a common pattern of forced T AC (x, t) changes in observations and in the five LEs. The key processes involved include GHG-induced expansion of the tropics, lapse-rate changes, land surface drying, and sea ice decrease.

54 ENVIRONMENTAL SCIENCES↗

The global decline in the sensitivity of vegetation productivity to precipitation from 2001 to 2018

The sensitivity of vegetation productivity to precipitation (S ppt ) is a key metric for understanding the variations in vegetation productivity under changing precipitation and predicting future changes in ecosystem functions. However, a comprehensive assessment of S ppt over all the global land is lacking. Here, we investigated spatial patterns and temporal changes of S ppt across the global land from 2001 to 2018 with multiple streams of satellite observations. We found consistent spatial patterns of S ppt with different satellite products: S ppt was highest in dry regions while low in humid regions. Grassland and shrubland showed the highest S ppt , and evergreen needle-leaf forest and wetland showed the lowest. Temporally, S ppt showed a generally declining trend over the past two decades (p < .05), yet with clear spatial heterogeneities. The decline in S ppt was especially noticeable in North America and Europe, likely due to the increase in precipitation. In central Russia and Australia, however, S ppt showed an increasing trend. Biome-wise, most ecosystem types exhibited significant decrease in S ppt , while grassland, evergreen broadleaf forest, and mixed forest showed slight increases or non-significant changes in S ppt . Our finding of the overall decline in S ppt implies a potential stabilization mechanism for ecosystem productivity under climate change. However, the revealed S ppt increase for some regions and ecosystem types, in particular global grasslands, suggests that grasslands might be increasingly vulnerable to climatic variability with continuing global climate change.

54 ENVIRONMENTAL SCIENCES↗

Increased frequency of planetary wave resonance events over the past half-century

We demonstrate a tripling in the frequency of planetary wave resonance events over the past halfcentury, coinciding with the rise in persistent boreal summer weather extremes. This increase aligns with changes in the underlying climate conditions favoring these events, including amplified Arctic warming and land-sea thermal contrast. We also observe increased prevalence of resonant amplification events following the mature phase of strong El Niño events, suggesting that such events may precondition the mean state conditions in ways that favor large-scale quasi-stationary wave patterns and quasi-resonant wave amplification. Since the impact of anthropogenic warming on quasi-resonant amplification is not well captured by current-generation climate models, it is likely that models are underpredicting the potential increase, indicating even greater risk of persistent extreme summer weather events with ongoing warming.

Arctic amplification↗

Reducing stomatal density by expression of a synthetic epidermal patterning factor increases leaf intrinsic water use efficiency and reduces plant water use in a C4 crop

Abstract Enhancing crop water use efficiency (WUE) is a key target trait for climatic resilience and expanding cultivation on marginal lands. Engineering lower stomatal density to reduce stomatal conductance (gs) has improved WUE in multiple C3 crop species. However, reducing gs in C3 species often reduces photosynthetic carbon gain. A different response is expected in C4 plants because they possess specialized anatomy and biochemistry which concentrates CO2 at the site of fixation. This modifies the relationship of photosynthesis (AN) with intracellular CO2 concentration (ci), such that photosynthesis is CO2 saturated and reductions in gs are unlikely to limit AN. To test this hypothesis, genetic strategies were investigated to reduce stomatal density in the C4 crop sorghum. Constitutive expression of a synthetic epidermal patterning factor (EPF) transgenic allele in sorghum led to reduced stomatal densities, reduced gs, reduced plant water use, and avoidance of stress during a period of water deprivation. In addition, moderate reduction in stomatal density did not increase stomatal limitation to AN. However, these positive outcomes were associated with negative pleiotropic effects on reproductive development and photosynthetic capacity. Avoiding pleiotropy by targeting expression of the transgene to specific tissues could provide a pathway to improved agronomic outcomes.

59 BASIC BIOLOGICAL SCIENCES↗

Future Climate Impacts of Direct Radiative Forcing Anthropogenic Aerosols, Tropospheric Ozone, and Long-lived Greenhouse Gases

Long-lived greenhouse gases (GHGs) are the most important driver of climate change over the next century. Aerosols and tropospheric ozone (O3) are expected to induce significant perturbations to the GHG-forced climate. To distinguish the equilibrium climate responses to changes in direct radiative forcing of anthropogenic aerosols, tropospheric ozone, and GHG between present day and year 2100, four 80-year equilibrium climates are simulated using a unified tropospheric chemistry-aerosol model within the Goddard Institute for Space Studies (GISS) general circulation model (GCM) 110. Concentrations of sulfate, nitrate, primary organic (POA) carbon, secondary organic (SOA) carbon, black carbon (BC) aerosols, and tropospheric ozone for present day and year 2100 are obtained a priori by coupled chemistry-aerosol GCM simulations, with emissions of aerosols, ozone, and precursors based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenario (SRES) A2. Changing anthropogenic aerosols, tropospheric ozone, and GHG from present day to year 2100 is predicted to perturb the global annual mean radiative forcing by +0.18 (considering aerosol direct effects only), +0.65, and +6.54 W m(sup -2) at the tropopause, and to induce an equilibrium global annual mean surface temperature change of +0.14, +0.32, and +5.31 K, respectively, with the largest temperature response occurring at northern high latitudes. Anthropogenic aerosols, through their direct effect, are predicted to alter the Hadley circulation owing to an increasing interhemispheric temperature gradient, leading to changes in tropical precipitation. When changes in both aerosols and tropospheric ozone are considered, the predicted patterns of change in global circulation and the hydrological cycle are similar to those induced by aerosols alone. GHG-induced climate changes, such as amplified warming over high latitudes, weakened Hadley circulation, and increasing precipitation over the Tropics and high latitudes, are consistent with predictions of a number of previous GCM studies. Finally, direct radiative forcing of anthropogenic aerosols is predicted to induce strong regional cooling over East and South Asia. Wintertime rainfall over southeastern China and the Indian subcontinent is predicted to decrease because of the increased atmospheric stability and decreased surface evaporation, while the geographic distribution of precipitation is also predicted to be altered as a result of aerosol-induced changes in wind flow.

Chen, Wei-Ting↗

The Response of the Ozone Layer Under Abrupt 4xCO2 in CMIP6

Previous studies indicate a possible role of stratospheric ozone chemistry feedbacks in the climate response to 4xCO2, either via a reduction in equilibrium climate sensitivity (ECS) (Nowack et al.,2015), or via changes in the tropospheric circulation (Chiodo and Polvani, 2017). However, these effects are subject to uncertainty. Part of the uncertainty may stem from the dependency of the feedback on the pattern of the ozone response, as the radiative efficiency of ozone largely depends on its vertical distribution (Lacis et al., 1990). Here, an analysis is presented of the ozone layer response to 4xCO2 in chemistry–climate models (CCMs) which participated to CMIP intercomparisons. In a previous study using CMIP5 models, it has been shown that under 4xCO2, ozone decreases in the tropical lower stratosphere, and increases over the high latitudes and throughout the upper stratosphere. It was also found that a substantial portion of the spread in the tropical column ozone is tied to inter-model spread in tropical upwelling, which is in turn tied to ECS (Chiodo et al., 2018). Here, we revisit this connection using 4xCO2 data from CMIP6, thereby exploiting the larger number of CCMs than in CMIP5. In addition, we explore the linearity of the ozone response, by complementing the analysis with simulations using lower CO 2 forcing levels (2xCO2). We show that the pattern of the ozone response in is similar to CMIP5. In some models (e.g. WACCM), we find larger ozone responses in CMIP6 than in CMIP5, partly because of the larger ECS and thus larger upwelling response in the tropical pipe. In this presentation, we will discuss the relationship between radiative forcing, transport and ozone, as well as further implications for CMIP6 models.

Ozone layer↗

ENSO and MJO Modulation of U.S. Cloud-to-Ground Lightning Activity

Cloud-to-ground (CG) lightning substantially impacts human health and property. However, the relations between U.S. lightning activity and the Madden-Julian Oscillation (MJO) and El Niño-Southern Oscillation (ENSO), two predictable drivers of global climate variability, remain uncertain, in part because most lightning datasets have short records that cannot robustly reveal MJO- and ENSO-related patterns. To overcome this limitation, we developed an empirical model of 6-hourly lightning flash count over the contiguous U.S. (CONUS) using environmental variables (convective available potential energy and precipitation) andNational Lightning Detection Network data for 2003–2016. This model is shown to reproduce the observed daily and seasonal variability of lightning over most of CONUS. Then, the empirical model was applied to construct a proxy lightning dataset for the period 1979–2021, which was used to investigate the summer MJO-lightning relationship at daily resolution and the winter-spring ENSO-lightning relationship at seasonal resolution. Overall, no robust relationship between MJO phase and lightning patterns was found when seasonality was taken into consideration. El Niño is associated with increased lightning activity over the Coastal Southeast U.S. during early winter, the Southwest during winter through spring, and the Northwest during late spring, whereas La Niña is associated with increased lightning activity over the Tennessee River Valley during winter.

Lightning↗

Regional patterns in hydrologic response, a new three-component metric for hydrograph analysis and implications for ecohydrology, Northwest Volcanic Aquifer Study Area, USA

Spatial patterns of hydrologic response were examined for the Northwest Volcanic Aquifer Study Area (NVASA). The utility of established hydrograph-separation methods for assessing hydrologic response in permeable volcanic terranes was assessed and a new three-component metric for hydrograph analysis was developed. The new metric, which partitions streamflow into subcomponents defined by the timescales of hydrologic response (e.g., fast-runoff, intermediate-interflow and slow-baseflow), was used to gain a fundamental understanding of the regional hydrology, investigate sub-regional differences, influencing factors, and ecohydrological implications. The combined effects of NVASA’s physiography, climate and geology create a strongly coupled surface-groundwater system that produces copious baseflow and limited quantities of runoff and interflow. Patterns of hydrologic response are influenced by the type and rate of precipitation and permeability of the underlying geology. Under variable precipitation conditions the hydrologic response of volcanic terranes with similar permeability and subsurface-storage capacity can be significantly different. From a water management and ecohydrology perspective, understanding regional patterns of hydrologic response and sub-regional differences is fundamental. Results indicate that minimum-flow methods provide the most conservative estimate of baseflow and may be the most robust for filtering out snowmelt bias in baseflow estimates. Baseflow contributes ~75% of the perennial streamflow across the NVASA and represents a critical component of the regional water supply that provides critical cold-water habitat.

54 ENVIRONMENTAL SCIENCES↗

Spatiotemporal Variations of Evapotranspiration in Amazonia Using the Wavelet Phase Difference Analysis

The relationships and seasonal-to-annual variations among evapotranspiration (ET), precipitation (P), terrestrial water storage anomalies (TWSA), radiation (downward shortwave radiation, DSR), and phenology (leaf area index, LAI) are complex across the Amazon basin. Here, to analyze how ET is controlled by these influencing factors, we used wavelet phase difference (WPD) to investigate the effects of P, TWSA, DSR, and LAI on ET at different spatiotemporal scales. The Amazon-scale averaged ET has strong correlations with these factors at the annual and multi-year periodicities. The patterns of WPDs have south-north and west-east divides due to the significant variation in climatic conditions. The results demonstrate that ET is mainly affected by water and energy availability while vegetation regulates both processes. The deep soil moisture/groundwater can provide strong subsidies to ET during the meteorological dry season in the water-limited area of Amazon. The WPD can well reflect the responses of ET to the variations of P, TWSA, DSR, and LAI, and the process of vegetation sustaining ET in the dry years in the water-limited area of the Amazon.

54 ENVIRONMENTAL SCIENCES↗