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NASA NTRS2015

Causes of the 2011-14 California Drought

The causes of the California drought during November-April winters of 2011/12-2013/14 are analyzed using observations and ensemble simulations with seven atmosphere models forced by observed SSTs. Historically, dry California winters are most commonly associated with a ridge off the west coast but no obvious SST forcing. Wet winters are most commonly associated with a trough off the west coast and an El Nino event. These attributes of dry and wet winters are captured by many of the seven models. According to the models, SST forcing can explain up to a third of California winter precipitation variance. SST forcing was key to sustaining a high pressure ridge over the west coast and suppressing precipitation during the three winters. In 2011/12 this was a response to a La Nina event, whereas in 2012/13 and 2013/14 it appears related to a warm west-cool east tropical Pacific SST pattern. All models contain a mode of variability linking such tropical Pacific SST anomalies to a wave train with a ridge off the North American west coast. This mode explains less variance than ENSO and Pacific decadal variability, and its importance in 2012/13 and 2013/14 was unusual. The models from phase 5 of CMIP (CMIP5) project rising greenhouse gases to cause changes in California all-winter precipitation that are very small compared to recent drought anomalies. However, a long-term warming trend likely contributed to surface moisture deficits during the drought. As such, the precipitation deficit during the drought was dominated by natural variability, a conclusion framed by discussion of differences between observed and modeled tropical SST trends.

California Drought↗

NASA NTRSDate not supplied

Detecting Short Term Drought Impact in the Southwest US Using GOES-16 ABI Data

Satellite optical remote sensing has been often used for monitoring broad-region vegetation change, for example, phenology observations and the year-to-year leaf area index (LAI) responses to climate oscillations. However, rapid responses of vegetation to day-to-day weather perturbations are difficult to detect using available optical remote sensing satellites because of the low frequency of the observations. Sun-synchronous optical sensors, such as Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR), can observe a target area once a day. Daily observations cannot distinguish whether short-term changes in Normalized Differential Vegetation Index (NDVI) are actual LAI change or cloud contamination. NOAA’s GOES satellites make observations every 10 to 15 minutes using the Advanced Baseline Imager (ABI). In this study, we used the Geostationary-NASA Earth Exchange (GeoNEX) L1G Top-of-Atmosphere (TOA) ABI data to detect drought impact on NDVI time series in the Southwest US. We used an empirical method to cancel the BRDF effect of varying solar zenith angle. The ABI was able to detect short term drought impacts as well as an NDVI decrease in the dry season. Increased NDVI right after a rainfall followed by an immediate decrease was observed. These ABI NDVI changes were correlated with the RGB time series from PhenoCam Network data. Results indicated that the ABI can be used for short-term analysis of LAI and can detect small LAI changes caused by drought in an arid area, suggesting the potential for its use in near-real time drought monitoring applications.

ABI↗

NASA NTRS2020

Towards a Soil Moisture Drought Monitoring System for South Korea

The Korea Land Data Assimilation System (KLDAS) has been established for agricultural drought (i.e. soil moisture deficit) monitoring in South Korea, running the Noah-MP land surface model within the NASA Land Information System (LIS) framework with the added value of local precipitation forcing dataset and soil texture maps. KLDAS soil moisture is benchmarked against three global products: the Global Land Data Assimilation System (GLDAS), the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), and the European Space Agency Climate Change Initiative (ESA CCI) satellite product. The evaluation is performed using in situ measurements for 2013–2015 and one month standardized precipitation index (SPI-1) for 1982–2016, focusing on four major river basins in South Korea. The KLDAS outperforms all benchmark products in capturing soil moisture states and variability at a basin scale. Compared to GLDAS and FLDAS products, the EAS CCI product is not feasible for long term agricultural monitoring due to lower data quality for early periods (1979–1991) of soil moisture estimates. KLDAS shows that the most recent 2015 drought event leads to highest drought areas in the Han and Geum River basins in the past 35 years. This work supports KLDAS as an effective agricultural drought monitoring system to provide continuous regional high-resolution soil moisture estimates in South Korea.

Agricultural drought↗

NASA NTRS2021

Severity of Drought and Heatwave Crop Losses Tripled Over the Last Five Decades in Europe

Extreme weather disasters (EWDs) can jeopardize domestic food supply and disrupt commodity markets. However, historical impacts on European crop production associated with droughts, heatwaves, floods, and cold waves are not well understood—especially in view of potential adverse trends in the severity of impacts due to climate change. Here, we combine observational agricultural data (FAOSTAT) with an extreme weather disaster database (EM-DAT) between 1961 and 2018 to evaluate European crop production responses to EWD. Using a compositing approach (superposed epoch analysis), we show that historical droughts and heatwaves reduced European cereal yields on average by 9% and 7.3%, respectively, associated with a wide range of responses (inter-quartile range +2% to −23%; +2% to −17%). Non-cereal yields declined by 3.8% and 3.1% during the same set of events. Cold waves led to cereal and non-cereal yield declines by 1.3% and 2.6%, while flood impacts were marginal and not statistically significant. Production losses are largely driven by yield declines, with no significant changes in harvested area. While all four event frequencies significantly increased over time, the severity of heatwave and drought impacts on crop production roughly tripled over the last 50 years, from −2.2% (1964–1990) to −7.3% (1991–2015). Drought-related cereal production losses are shown to intensify by more than 3% yr−1. Both the trend in frequency and severity can possibly be explained by changes in the vulnerability of the exposed system and underlying climate change impacts.

Extreme weather disasters↗

NASA NTRSDate not supplied

NASA SPoRT-Land Information System and Vegetation Stress Real-Time Products for Drought, Wildfire, and Pluvial Analysis

The NASA SPoRT Center has been producing a near real-time instance of the NASA Land Information System over a CONUS domain (hereafter “SPoRT-LIS”) since ~2015. The SPoRT-LIS runs the legacy Noah LSM in an observations-constrained manner, with outputs of soil moisture and temperature at layered depths along with surface energy fluxes. The unique configuration of SPoRT-LIS enables decision-making on operational timescales since it incorporates near real-time observations such as VIIRS Green Vegetation Fraction and MRMS QPE. An additional in-house Alaska-LIS is produced in real time to help inform end-users on spring snow melt and summer soil moisture trends during the wildfire season. Use of the SPoRT-LIS has gradually expanded in recent years as a component of drought analysis, feedback to the USDM, and is utilized by State Climate Offices. Operational feedback has led to increased applicability for analyses by other end-users in the drought community. This presentation will provide SPoRT-LIS applications for drought, pluvial, and fire weather case-studies. We will also present preliminary results of 2-week SPoRT-LIS forecast percentiles that were recently implemented using GFS model forecast fields. We will additionally discuss the pathway toward extending these forecasts into the future by incorporating ensemble forecasts for probabilistic guidance on soil moisture trends for potential flash drought and subseasonal outlooks.

Soil Moisture↗

NASA NTRS2022

Idaho Wildfires II: Assessing the Relationship Between Drought Indicators and Wildfire Risk to Enhance Hazard Modeling and Inform Mitigation Planning

The western United States has experienced twenty years of increased and prolonged drought which have exacerbated wildfire hazards. These jeopardize population centers through increased risks to ecosystem services, local economies, and livelihoods. The Idaho Office of Emergency Management, Water Resources, and Department of Lands are seeking methods to dynamically monitor these conditions and update models that inform hazard mitigation planning and resource allocation. Towards this, these agencies partnered with NASA DEVELOP to produce drought-enhanced wildfire hazard models. Part of a two-term project, the two teams revised the state’s static wildfire hazard model with refined data layers and remotely-sensed data to reflect dynamic ecosystem responses to drought conditions and wildfire potential. Our team distinguished between rangeland and forestland ecosystems, and investigated relationships between drought metrics and vegetation condition using TerrSet Earth Trends Modeler. This analysis determined that total precipitation at a 5-month lag interval (r 2 = 0.72) along with the Evaporative Stress Index (r 2 = 0.69); and precipitation at a 5-month interval (r 2 = 0.42) were important drivers in rangeland and forestland, respectively. These driver variables were incorporated into a temporally dynamic wildfire hazard map. Our team used linear regression to correlate hazard ratings with wildfire frequency. For the year 2020, neither the enhanced hazard model (p < 0.10, r 2 = 0.01) nor the state’s static model (p < 0.05, r 2 = 0.03) were strongly correlated with actual wildfire frequency as they expressed an inverse relationship between wildfire hazard and frequency. This suggests wildfire occurrence is complex and not necessarily driven by the variables used.

Wildfire↗

NASA NTRS1992

Issues in establishing causes of the 1988 drought over North America

The causes and physical mechanisms involved in the 1988 North American drought are investigated. The issue of when the drought circulation anomalies developed and their relation to changes in tropical Pacific SSTs is examined. The evolution of the Pacific SSTs and tropical convection, as revealed by outgoing LW radiation, is shown to be consistent with the development of the conditions favorable for initiating the drought circulation pattern in April through June of 1988. On the equator at 110 deg W, SST anomalies exceeded -2.75 C only in April, May, and June, and were largest (-4.1 C) in May 1988. Diagnostic calculations of atmospheric diabatic heating confirm that atmospheric heating anomalies existed in the tropical Pacific in association with the major SST anomalies during this time. It is argued that feedback-caused soil moisture anomalies were secondary sources for the drought circulation but could not have been the primary instigator.

Trenberth, Kevin E.↗

NASA NTRS1994

Vegetation stress as a feedback mechanism in midlatitude drought

An atmospheric general circulation model with land surface properties represented by the Simplified Simple Biosphere Model is used to investigate the effect of soil moisture and vegetation stress on drought in the mid-latitudes. An idealized land-sea distribution with simple topography is used to remove as many external sources of climate variation as possible. The land consists of a single, flat, rectangular continent covered with prairie vegetation and centered on 44 deg N of an aqua planet. A control integration of 4 years is performed, and several sets of seasonal anomaly integrations are made to test the sensitivity of seasonal climate to low initial (1 April) soil moisture and dormant vegetation like what would occur during a severe drought. It is found that the inclusion of dormant vegetation during the spring and early summer greatly reduces evapotranspiration by eliminating transpiration. This affects local climate more strongly as summer progresses. Low initial soil moisture, combined with dormant vegetation, leads to a severe drought. The reduction in precipitation is much greater in magnitude than that due to low soil moisture alone, and greater than the sum of the effects computed separately. Although the short-term drought is more severe, the dormancy of the vegetation prevents further depletion of moisture in the root zone of the soil, so soil moisture begins to rebound toward the middle of summer.

Dirmeyer, Paul A.↗

NASA NTRS2002

On Simulating the Mid-western-us Drought of 1988 with a GCM

The primary cause of the midwestern North American drought in the summer of 1988 has been identified to be the La Nina SST anomalies. Yet with the SST anomalies prescribed, this drought has not been simulated satisfactorily by any general circulation model. Seven simulation-experiments, each containing an ensemble of 4-sets of simulations, were conducted with the GEOS GCM for both 1987 and 1988. All simulations started from January 1 and continued through the end of August. In the first baseline case, Case 1, only the SST anomalies and some vegetation parameters were prescribed, while everything else (such as soil moisture, snow-cover, and clouds) was interactive. The GCM did produce some of the circulation features of a drought over North America, but they could only be identified on the planetary scales. The 1988 minus 1987 precipitation differences show that the GCM was successful in simulating reduced precipitation in the mid-west, but the accompanying circulation anomalies were not well simulated, leading one to infer that the GCM has simulated the drought for the wrong reason. To isolate the causes for this unremarkable circulation, analyzed winds and soil moisture were prescribed in Case 2 and Case 3 as continuous updates by direct replacement of the GCM-predicted fields. These cases show that a large number of simulation biases emanate from wind biases that are carried into the North American region from surroundings regions. Inclusion of soil moisture also helps to ameliorate the strong feedback, perhaps even stronger than that of the real atmosphere, between soil moisture and precipitation. Case 2 simulated one type of surface temperature anomaly pattern, whereas Case 3 with the prescribed soil moisture produced another.

Sud, Y. C.↗

NASA NTRS2009

A USCLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results

The USCLI VAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. Specific questions that the runs are designed to address include: What are the mechanisms that maintain drought across the seasonal cycle and from one year to the next? What is the role of the leading patterns of SST variability, and what are the physical mechanisms linking the remote SST forcing to regional drought, including the role of land-atmosphere coupling? The runs were carried out with five different atmospheric general circulation models (AGCM5), and one coupled atmosphere-ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Nino/Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic Multi-decadal Oscillation (AMO), and a global trend pattern. One of the key findings is that all the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the U.S. tends to occur when the two oceans have anomalies of opposite sign. That is, a cold Pacific and warm Atlantic tend to produce the largest precipitation reductions, whereas a warm Pacific and cold Atlantic tend to produce the greatest precipitation enhancements. Further analysis of the response over the U.S. to the Pacific forcing highlights a number of noteworthy and to some extent unexpected results. These include a seasonal dependence of the precipitation response that is characterized by signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. Another interesting result concerns what appears to be a substantially different character in the surface temperature response over the U.S. to the Pacific forcing by the only model examined here that was developed for use in numerical weather prediction. The response to the positive SST trend forcing pattern is an overall surface warming over the world's land areas with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all the models.

Schubert, Siegfried↗

NASA NTRS2012

Assimilation of GRACE Terrestrial Water Storage into a Land Surface Model: Evaluation 1 and Potential Value for Drought Monitoring in Western and Central Europe

A land surface model s ability to simulate states (e.g., soil moisture) and fluxes (e.g., runoff) is limited by uncertainties in meteorological forcing and parameter inputs as well as inadequacies in model physics. In this study, anomalies of terrestrial water storage (TWS) observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission were assimilated into the NASA Catchment land surface model in western and central Europe for a 7-year period, using a previously developed ensemble Kalman smoother. GRACE data assimilation led to improved runoff correlations with gauge data in 17 out of 18 hydrological basins, even in basins smaller than the effective resolution of GRACE. Improvements in root zone soil moisture were less conclusive, partly due to the shortness of the in situ data record. In addition to improving temporal correlations, GRACE data assimilation also reduced increasing trends in simulated monthly TWS and runoff associated with increasing rates of precipitation. GRACE assimilated root zone soil moisture and TWS fields exhibited significant changes in their dryness rankings relative to those without data assimilation, suggesting that GRACE data assimilation could have a substantial impact on drought monitoring. Signals of drought in GRACE TWS correlated well with MODIS Normalized Difference Vegetation Index (NDVI) data in most areas. Although they detected the same droughts during warm seasons, drought signatures in GRACE derived TWS exhibited greater persistence than those in NDVI throughout all seasons, in part due to limitations associated with the seasonality of vegetation.

Li, Bailing↗

NASA NTRS2015

Assessment of the 2013-2014 Drought on Ecosystems of the California Central Coast

Calendar year 2013 was the driest on record in California, with a total of just 30 percent of average statewide precipitation. The objective of this present study was to assess the impacts of the historic 2013-2014 drought on ecosystems of the Central Coast region using a combination of satellite image analysis and in situ measurements of soil moisture. According to differences in Landsat NDWI and NDVI between May of 2010 and 2013, the geographic areas within the study region that were most severely impacted by the 2013 drought were the inland Carmel Valley in northern Monterey County, and the coast zones around San Simeon Point and Cambria in northern San Luis Obispo County. For more detailed examination of drought impacts, the entire study region was separated into the three predominate vegetation types (grasslands, shrublands, and forests) to examine changes in Landsat NDWI and NDVI in the context of differing plant community response to severe drought.

Normalized Differences Vegetation Index (NDVI)↗

NASA NTRS2018

El Nino Drought Increased Canopy Turnover in Amazon Forests

Amazon droughts, including the 2015-2016 El Ni~no, may reduce forest net primary productivityand increase canopy tree mortality, thereby altering both the short- and the longtermnet forest carbon balance. Given the broad extent of drought impacts, inventory plots oreddy flux towers may not capture regional variability in forest response to drought. We used multi-temporal airborne Lidar data and field measurements of coarse woodydebris to estimate patterns of canopy turnover and associated carbon losses in intact and fragmentedforests in the central Brazilian Amazon between 2013-2014 and 2014-2016. Average annualized canopy turnover rates increased by 65% during the drought period inboth intact and fragmented forests. The average size and height of turnover events was similarfor both time intervals, in contrast to expectations that the 2015-2016 El Ni~no droughtwould disproportionally affect large trees. Lidar biomass relationships between canopyturnover and field measurements of coarse woody debris were modest (R2 0.3), given similarcoarse woody debris production and Lidar-derived changes in canopy volume from singletree and multiple branch fall events. Our findings suggest that El Ni~no conditions accelerated canopy turnover in central Amazonforests, increasing coarse woody debris production by 62% to 1.22 Mg C ha1(exp) yr1(exp) indrought years.

ecosystem models↗

NASA NTRS2019

Evaluating the Operational Application of SMAP for Global Agricultural Drought Monitoring

Over the past two decades, remote sensing has made possible the routine global monitoring of surface soil moisture. Regionalagricultural drought monitoring is one of the most logicalapplication areas for such monitoring. However, remote sensing alone provides soil moisture information for only the top few centimetersof the soil profile, while agricultural drought monitoring requires knowledge of the amount of water present in the entireroot zone. The assimilation of remotely sensed soil moisture productsinto continuous soil water balance models provides a way ofaddressing this shortcoming. Here, we describe the assimilationof NASA's soil moisture active passive (SMAP) surface soil moisture data into the United States Department of Agriculture Foreign Agricultural Service (USDA FAS) Palmer model and assess the impactof SMAP on USDA FAS drought monitoring capabilities. Theassimilation of SMAP is specifically designed to enhance the model skill and the USDA FAS drought capabilities by correcting for randomerrors inherent in its rainfall forcing data. The performanceof this SMAP-based assimilation system is evaluated using two approaches.At global scale, the accuracy of the system is assessed by examining the lagged correlation agreement between soil moistureand the normalized difference vegetation index (NDVI). Additional regional-scale evaluation using in situ-based soil moisture estimatesis carried out at seven of the SMAP core Cal/Val sites located in theUSA. Both types of analysis demonstrate the value of assimilating SMAP into the USDA FAS Palmer model and its potential to enhance operational USDA FAS root-zone soil moisture information.

Mladenova, Iliana E.↗

NASA NTRS2020

Developing a Customized Composite Drought Index for Pakistan

Pakistan experiences frequent and intense agricultural drought, varying spatially and temporally. Prolonged dry conditions often result in failed crop production. Using multiple variables, different components of drought can be captured across a multitude of climatic zones and throughout different seasons. Developing a composite drought index (CDI), specific for each district, will provide a more complete view of agricultural drought and enhance early warning systems.

Schwartz, Caily↗

NASA NTRSDate not supplied

Modeling the Worst-Case-Scenario of Soil Drydown for Agricultural Drought Monitoring in Kansas Using NASA Earth Observations and In-situ Parameters

Climatologists in Kansas have observed rapid shifts from wet to dry conditions and rapid intensification of drought conditions for the state in recent years. As a leading state in agricultural production, drought events can lead to decreased crop yields and impact the state’s economy. The exponential decay of soil moisture content is a major consequence of drought and can exacerbate these impacts on agricultural production. This study examined the rate of soil moisture drydown in Kansas to understand and monitor the worst-case-scenario of short-term soil water shortage. Soil Moisture Active Passive (SMAP) L-band Radiometer rootzone soil moisture imagery from March 2015 to June 2019 was used to estimate the minimum and maximum soil moisture capacity throughout the state. In situ soil moisture parameters, such as the exponential decay constant, were approximated from the Kansas Mesonet system. These variables were inputs into an exponential decay model that forecasted gridded rootzone soil moisture in a scenario that assumed no precipitation for a user-identified period of time. The forecasts were output on the order of weeks to capture the rapid shifts in soil moisture content. Another model was used to identify areas in Kansas currently below a given percentage of the relative soil moisture saturation, measured as a function of minimum, maximum, and current soil moisture. This model forecasted the number of days until each cell in the soil moisture grid reached the input percentage of relative soil moisture saturation. The gridded model outputs and workflow were developed in partnership with the Kansas Water Office and Kansas Office of the State Climatologist at Kansas State University, as a part of their drought monitoring efforts.

NASA DEVELOP↗

NASA NTRS2021

Illinois Disasters: Utilizing NASA Earth Observations to Enhance Drought Monitoring in Illinois

Drought and flooding in Illinois have severe impacts on the communities and ecosystems of the state. Soil moisture is a valuable indicator of drought and flood vulnerability but can be difficult to measure since in situ monitoring is limited to discrete stations throughout the state. The team created a framework to compare in situ, modeled, and NASA satellite soil moisture measurements to increase the spatial coverage of soil moisture monitoring. The team partnered with the Illinois State Weather Survey, USDA Midwest Climate Hub, NOAA Regional Climate Services of the Central Region, NOAA National Integrated Drought Information System’s Midwest Drought Early Warning System, and the NOAA North Central River ForecastCenter. The team standardized and compared soil moisture data from NASA’s Soil Moisture Active Passive (SMAP) mission, modeled soil moisture outputs from NASA’s SPoRT Land Information System (SPoRT-LIS), and in situ measurements from the Illinois State Weather Survey’s Water and Atmospheric Resources Monitoring (WARM) program. Compared to the WARM data, the satellite and modeled data showed seasonally variable differences and bias. The difference was highest in the winter months and lowest in the late summer and early fall months for the SMAP and SPoRT-LIS data products. SPoRT-LIS produced lower seasonal variability and SMAP demonstrated higher correlation values and lower differences. These analyses suggest that both SMAP and SPoRT-LIS products offer unique strengths and limitations when used for soil moisture monitoring

Joshua Green↗

NASA NTRS2021

Improving Flood and Drought Management in Agricultural River Basins: An Application to the Mun River Basin in Thailand

Agriculture productivity is regularly affected by floods and droughts, and the severity is likely to increase in the future. Even if significant efforts are spent on water development projects, ineffective project planning often means that they continue to occur or are only partly mitigated, for example, in the Mun River Basin, Thailand, where 1000s of water projects have been implemented. Despite this, the basin regularly experiences floods and droughts. In this study, an analysis of the adverse impacts of basin-scale floods and droughts on rice cultivation in the Mun River Basin is conducted, and an estimation of the coping capacity of existing measures. The results demonstrate that while the total storage capacity of in-situ and ongoing projects would be sufficient to tackle both hazards, it can only be achieved if the projects are effectively utilised. Based on this, proposed solutions for the region include small farm ponds, a subsurface floodwater harvesting system, and oxbow lake reconnections. The suggested measures are practicable, economical, environmentally low-impact, and their implementation (if executed with appropriate care) would reduce flood and drought problems in the basin. Notably, the measures and calculation methods proposed for this basin can also be applied to other crops and regions.

Farm pond↗