scholarly journals Why Do Different Drought Indices Show Distinct Future Drought Risk Outcomes in the U.S. Great Plains?

2017 ◽  
Vol 30 (1) ◽  
pp. 265-278 ◽  
Author(s):  
Song Feng ◽  
Miroslav Trnka ◽  
Michael Hayes ◽  
Yongjun Zhang
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Surface Soil ◽  
Drought Indices ◽  
Drought Risk ◽  
Short Term ◽  
The Future ◽  
Total Column ◽  
The U.S

Vigorous discussions and disagreements about the future changes in drought intensity in the U.S. Great Plains have been taking place recently within the literature. These discussions have involved widely varying estimates based on drought indices and model-based projections of the future. To investigate and understand the causes for such a disparity between these previous estimates, the authors analyzed the soil moisture at the near-surface soil layer and the entire soil column, as well as the Palmer drought severity index, the Palmer Z index, and the standardized precipitation and evaporation index using the output from the Community Climate System Model, version 4 (CCSM4), and 25 state-of-the-art climate models. These drought indices were computed using potential evapotranspiration estimated by the physically based Penman–Monteith method (PE_pm) and the empirically based Thornthwaite method (PE_th). The results showed that the short-term drought indices are similar to modeled surface soil moisture and show a small but consistent drying trend in the future. The long-term drought indices and the total column soil moisture, however, are consistent in projecting more intense future drought. When normalized, the drought indices with PE_th all show unprecedented future drying, while the drought indices with PE_pm show comparable dryness with the modeled soil moisture. Additionally, the drought indices with PE_pm are closely related to soil moisture during both the twentieth and twenty-first centuries. Overall, the drought indices with PE_pm, as well as the modeled total column soil moisture, suggest a widespread and very significant drying in the Great Plains toward the end of the century. The results suggest that the sharp contrasts about future drought risk in the Great Plains discussed in previous studies are caused by 1) comparing the projected changes in short-term droughts with that of the long-term droughts and/or 2) computing the atmospheric evaporative demand using an empirically based method (e.g., PE_th). The analysis here may be applied for drought projections in other regions across the globe.

scholarly journals Short-Term and Long-Term Surface Soil Moisture Memory Time Scales Are Spatially Anticorrelated at Global Scales

2019 ◽  
Vol 20 (6) ◽  
pp. 1165-1182 ◽  
Author(s):  
Kaighin A. McColl ◽  
Qing He ◽  
Hui Lu ◽  
Dara Entekhabi
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Time Scale ◽  
Surface Soil ◽  
Satellite Observations ◽  
Surface Soil Moisture ◽  
Short Term ◽  
Term Memory ◽  
Memory Time

Abstract Land–atmosphere feedbacks occurring on daily to weekly time scales can magnify the intensity and duration of extreme weather events, such as droughts, heat waves, and convective storms. For such feedbacks to occur, the coupled land–atmosphere system must exhibit sufficient memory of soil moisture anomalies associated with the extreme event. The soil moisture autocorrelation e-folding time scale has been used previously to estimate soil moisture memory. However, the theoretical basis for this metric (i.e., that the land water budget is reasonably approximated by a red noise process) does not apply at finer spatial and temporal resolutions relevant to modern satellite observations and models. In this study, two memory time scale metrics are introduced that are relevant to modern satellite observations and models: the “long-term memory” τL and the “short-term memory” τS. Short- and long-term surface soil moisture (SSM) memory time scales are spatially anticorrelated at global scales in both a model and satellite observations, suggesting hot spots of land–atmosphere coupling will be located in different regions, depending on the time scale of the feedback. Furthermore, the spatial anticorrelation between τS and τL demonstrates the importance of characterizing these memory time scales separately, rather than mixing them as in previous studies.

Improving Satellite-Based Rainfall Accumulation Estimates Using Spaceborne Surface Soil Moisture Retrievals

2009 ◽  
Vol 10 (1) ◽  
pp. 199-212 ◽  
Author(s):  
Wade T. Crow ◽  
George J. Huffman ◽  
Rajat Bindlish ◽  
Thomas J. Jackson
Keyword(s):  
Soil Moisture ◽  
Surface Soil ◽  
Rain Gauge ◽  
Surface Soil Moisture ◽  
Complementary Information ◽  
Short Term ◽  
Rain Gauge Data ◽  
Gauge Data ◽  
Cover Density

Abstract Over land, remotely sensed surface soil moisture and rainfall accumulation retrievals contain complementary information that can be exploited for the mutual benefit of both product types. Here, a Kalman filtering–based tool is developed that utilizes a time series of spaceborne surface soil moisture retrievals to enhance short-term (2- to 10-day) satellite-based rainfall accumulation products. Using ground rain gauge data as a validation source, and a soil moisture product derived from the Advanced Microwave Scanning Radiometer aboard the NASA Aqua satellite, the approach is evaluated over the contiguous United States. Results demonstrate that, for areas of low to moderate vegetation cover density, the procedure is capable of improving short-term rainfall accumulation estimates extracted from a variety of satellite-based rainfall products. The approach is especially effective for correcting rainfall accumulation estimates derived without the aid of ground-based rain gauge observations. Special emphasis is placed on demonstrating that the approach can be applied in continental areas lacking ground-based observations and/or long-term satellite data records.

scholarly journals Development and application of a short- /long-term composited drought index in the upper Huaihe River basin, China

2015 ◽  
Vol 369 ◽  
pp. 103-108
Author(s):  
M. Yu ◽  
Q. Li ◽  
G. Lu ◽  
H. Wang ◽  
P. Li
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Drought Index ◽  
The Self ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Short Term

Abstract. Accurate and reliable drought monitoring is of primary importance for drought mitigation and reduction of social-ecological vulnerability. The aim of the paper was to propose a short-term/long-term composited drought index (CDI) which could be widely used for drought monitoring and early warning in China. In the study, the upper Huaihe River basin above the Xixian gauge station, which has been hit by severe droughts frequently in recent decades, was selected as the case study site. The short-term CDI was developed by the Principle Component Analysis of the self-calibrating Palmer Drought Severity Index (sc-PDSI), the 1- and 3-month Standardized Precipitation Evapotranspiration Index (SPEI), Z Index (ZIND), the Soil Moisture Index (SMI) with the long-term CDI being formulated by use of the self-calibrating Palmer Hydrology Drought Index (sc-PHDI), the 6-, 12-, 18- and 24-month SPEI, the Standardized Streamflow Index (SSI), the SMI. The sc-PDSI, the PHDI, the ZIND, the SPEI on a monthly time scale were calculated based on the monthly air temperature and precipitation, and the monthly SMI and SSI were computed based on the simulated soil moisture and runoff by the distributed Xinanjiang model. The thresholds of the short-term/long-term CDI were determined according to frequency statistics of different drought indices. Finally, the feasibility of the two CDIs was investigated against the scPDSI, the SPEI and the historical drought records. The results revealed that the short-term/long-term CDI could capture the onset, severity, persistence of drought events very well with the former being better at identifying the dynamic evolution of drought condition while the latter better at judging the changing trend of drought over a long time period.

scholarly journals Assessment of Remotely Sensed and Modelled Soil Moisture Data Products in the U.S. Southern Great Plains

2020 ◽  
Vol 12 (12) ◽  
pp. 2030
Author(s):  
Bo Jiang ◽  
Hongbo Su ◽  
Kai Liu ◽  
Shaohui Chen
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Land Surface ◽  
European Space Agency ◽  
Remotely Sensed ◽  
The Other ◽  
Short Term ◽  
Southern Great Plains ◽  
The U.S

Soil moisture (SM) plays a crucial role in the water and energy flux exchange between the atmosphere and the land surface. Remote sensing and modeling are two main approaches to obtain SM over a large-scale area. However, there is a big difference between them due to algorithm, spatial-temporal resolution, observation depth and measurement uncertainties. In this study, an assessment of the comparison of two state-of-the-art remotely sensed SM products, Soil Moisture Active Passive (SMAP) and European Space Agency Climate Change Initiative (ESACCI), and one land surface modeled dataset from the North American Land Data Assimilation System project phase 2 (NLDAS-2), were conducted using 17 permanent SM observation sites located in the Southern Great Plains (SGP) in the U.S. We first compared the daily mean SM of three products with in-situ measurements; then, we decompose the raw time series into a short-term seasonal part and anomaly by using a moving smooth window (35 days). In addition, we calculate the daily spatial difference between three products based on in-situ data and assess their temporal evolution. The results demonstrate that (1) in terms of temporal correlation R, the SMAP (R = 0.78) outperforms ESACCI (R = 0.62) and NLDAS-2 (R = 0.72) overall; (2) for the seasonal component, the correlation R of SMAP still outperforms the other two products, and the correlation R of ESACCI and NLDAS-2 have not improved like the SMAP; as for anomaly, there is no difference between the remotely sensed and modeling data, which implies the potential for the satellite products to capture the variations of short-term rainfall events; (3) the distribution pattern of spatial bias is different between the three products. For NLDAS-2, it is strongly dependent on precipitation; meanwhile, the spatial distribution of bias represents less correlation with the precipitation for two remotely sensed products, especially for the SMAP. Overall, the SMAP was superior to the other two products, especially when the SM was of low value. The difference between the remotely sensed and modeling products with respect to the vegetation type might be an important reason for the errors.

scholarly journals Potential caveats in Land Surface Model evaluations using the U.S. Drought Monitor: roles of base periods and drought indicators

2021 ◽  
Author(s):  
Hailan Wang ◽  
Li Xu ◽  
Mimi Hughes ◽  
Muthuvel Chelliah ◽  
David G DeWitt ◽  
...  
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Water Model ◽  
Drought Indices ◽  
Surface Model ◽  
Short Term ◽  
Sst Variability ◽  
Drought Occurrence ◽  
The U.S

Abstract The U.S. Drought Monitor (USDM) has been widely used as an observational reference for evaluating Land Surface Model (LSM) simulation of drought. This study investigates potential caveats in such evaluation when the USDM and LSMs use different base periods and drought indices to identify drought. The retrospective National Water Model (NWM) v2.0 simulation (1993-2018) was used to exemplify the evaluation, supplemented by North American Land Data Assimilation System Phase 2 (NLDAS-2). In distinct contrast with the USDM which shows high drought occurrence (>50%) in the western half of the continental U.S. (CONUS) and the southeastern U.S. with low occurrence (<30%) elsewhere, the NWM and NLDAS-2 based on soil moisture percentiles (SMPs) consistently show higher drought occurrence (30-40%) in the central and southeastern U.S. than the rest of the CONUS. Much of the differences between the LSMs and USDM, particularly the strong LSM underestimation of drought occurrence in the western and southeastern U.S., are not attributed to the LSM deficiencies, but rather the lack of long-term drought in the LSM simulations due to their relatively short lengths. Specifically, the USDM integrates drought indices with century-long periods of record, which enables it to capture both short-term (<6 months) drought and long-term (>=6 months) drought, whereas the relatively short retrospective simulations of the LSMs allows them to adequately capture short-term drought but not long-term drought. In addition, the USDM integrates many drought indices whereas the NWM results are solely based on the SMP, further adding to the inconsistency. The high occurrence of long-term drought in the western and southeastern U.S. in the USDM is further found to be driven collectively by the post-2000 long-term warm SST trend, cold Pacific Decadal Oscillation (PDO) and warm Atlantic Multi-decadal Oscillation (AMO), all of which are typical leading patterns of global Sea Surface Temperature (SST) variability that can induce drought conditions in the western, central, and southeastern U.S. Our findings highlight the effects of the above caveats and suggest that LSM evaluation should stay qualitative when the caveats are considerable.

scholarly journals Analysis of the Relationship of U.S. Droughts with SST and Soil Moisture: Distinguishing the Time Scale of Droughts

2009 ◽  
Vol 22 (17) ◽  
pp. 4520-4538 ◽  
Author(s):  
Renguang Wu ◽  
James L. Kinter
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Boreal Summer ◽  
Medium Term ◽  
Short Term ◽  
Sst Forcing ◽  
Relationship Of ◽  
The Relationship ◽  
The Tropical Pacific

Abstract The impacts of droughts depend on how long droughts persist and the reasons why droughts extend to different time scales may be different. The present study distinguishes the time scale of droughts based on the standardized precipitation index and analyzes the relationship of boreal summer U.S. droughts with sea surface temperature (SST) and soil moisture. It is found that the roles of remote SST forcing and local soil moisture differ significantly for long-term and short-term droughts in the U.S. Great Plains and Southwest. For short-term droughts (≤3 months), simultaneous remote SST forcing plays an important role with an additional contribution from soil moisture. For medium-term and long-term droughts (≥6 months), both simultaneous and antecedent SST forcing contribute to droughts, and the soil moisture is important for the persistence of droughts through a positive feedback to precipitation. The antecedent remote SST forcing contributes to droughts through soil moisture and evaporation changes. The tropical Pacific SST is the dominant remote forcing for U.S. droughts. The most notable impacts of the tropical Pacific SST are found in the Southwest with extensions to the Great Plains. Tropical Indian Ocean SST forcing has a notable influence on medium-term and long-term U.S. droughts. The relationships between tropical Indian and Pacific Ocean SST and boreal summer U.S. droughts have undergone obvious long-term changes, especially for the Great Plains droughts.

The Future of Muslim Education in the United States: An Agenda for Research

2003 ◽  
Vol 20 (3-4) ◽  
pp. 46-82
Author(s):  
Fathi Malkawi
Keyword(s):  
United States ◽  
The United States ◽  
American Education ◽  
Future Trends ◽  
Muslim Community ◽  
Short Term ◽  
The Future ◽  
Muslim Education ◽  
Future Plans

This paper addresses some of the Muslim community’s concerns regarding its children’s education and reflects upon how education has shaped the position of other communities in American history. It argues that the future of Muslim education will be influenced directly by the present realities and future trends within American education in general, and, more importantly, by the well-calculated and informed short-term and long-term decisions and future plans taken by the Muslim community. The paper identifies some areas in which a wellestablished knowledge base is critical to making decisions, and calls for serious research to be undertaken to furnish this base.

scholarly journals Quantifying the Land–Atmosphere Coupling Behavior in Modern Reanalysis Products over the U.S. Southern Great Plains

2015 ◽  
Vol 28 (14) ◽  
pp. 5813-5829 ◽  
Author(s):  
Joseph A. Santanello ◽  
Joshua Roundy ◽  
Paul A. Dirmeyer
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Southern Great Plains ◽  
Diurnal Cycles ◽  
The North ◽  
Energy Cycle ◽  
Coupling Behavior ◽  
Regional Reanalysis ◽  
Modern Era ◽  
The U.S

Abstract The coupling of the land with the planetary boundary layer (PBL) on diurnal time scales is critical to regulating the strength of the connection between soil moisture and precipitation. To improve understanding of land–atmosphere (L–A) interactions, recent studies have focused on the development of diagnostics to quantify the strength and accuracy of the land–PBL coupling at the process level. In this paper, the authors apply a suite of local land–atmosphere coupling (LoCo) metrics to modern reanalysis (RA) products and observations during a 17-yr period over the U.S. southern Great Plains. Specifically, a range of diagnostics exploring the links between soil moisture, evaporation, PBL height, temperature, humidity, and precipitation is applied to the summertime monthly mean diurnal cycles of the North American Regional Reanalysis (NARR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and Climate Forecast System Reanalysis (CFSR). Results show that CFSR is the driest and MERRA the wettest of the three RAs in terms of overall surface–PBL coupling. When compared against observations, CFSR has a significant dry bias that impacts all components of the land–PBL system. CFSR and NARR are more similar in terms of PBL dynamics and response to dry and wet extremes, while MERRA is more constrained in terms of evaporation and PBL variability. Each RA has a unique land–PBL coupling that has implications for downstream impacts on the diurnal cycle of PBL evolution, clouds, convection, and precipitation as well as representation of extremes and drought. As a result, caution should be used when treating RAs as truth in terms of their water and energy cycle processes.

scholarly journals MENEJMEN RISIKO DALAM PERFEKTIF ISLAM

2017 ◽  
Vol 5 (1) ◽  
Author(s):  
Supriyo Supriyo
Keyword(s):  
Risk Management ◽  
Production System ◽  
Human Life ◽  
Short Term ◽  
Islamic Perspective ◽  
The Family ◽  
The Future ◽  
Short Run ◽  
A Company

Human life with all its activities in order to meet the needs of life always will always faced the possibility of risk either directly or indirectly, can occur in the short term or long term. A possibility of the occurrence or risk had certainly will affect the activity to be done And adversely affect the economy of a family and even a company, if the risks that occur have a vital impact on the family or an organization. Many failures within a company's organization are due to unforeseen risks occurring as for example the company never thinks that a newly established company is still in the short run abruptly because a workforce lacking control in the production system creates a great fire and spends all and has a bad impact For the economy of a family and even a company, if the risks that occur have a vital impact on the family or an organization. Many failures within a company's organization are due to unforeseen risks occurring as for example the company never thinks that a newly established company is still in the short run abruptly because a workforce lacking control in the production system creates a terrible fire and consumes all the company's assets Newly established. Everyone or anyone else would not want the incident to happen and befall themselves and his business in the future. Keywords: Islamic perspective, Risk management

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