Evaluation of remotely sensed precipitation sources for drought assessment in Semi-Arid Iraq

Suliman, Ali H. Ahmed; Awchi, Taymoor A.; Al-Mola, Mohammed Hussin Ahmed; Shahid, Shamsuddin

doi:10.1016/j.atmosres.2020.105007

Cited by 42 publications

(19 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These statistical metrics used include relative bias (RB), Pearson linear correlation coefficient (CC) and root mean square error (RMSE). These statistical indices have been used in many evaluation studies [15,16,49]. The equations are listed in Appendix A.…”

Section: Statistics Evaluation Metricsmentioning

confidence: 99%

“…Overall, the long latency of data acquisition, limited spatial representation, and data gaps in ground observations limit meteorological drought monitoring [13,14]. For example, many studies have lamented the scarcity of observations in Central Asia's arid zones [15,16]. Furthermore, to ensure the reliability of results, drought monitoring and event characterization require a long-term data period of at least 30 years [17].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of Three Long-Term Satellite-Based Precipitation Estimates against Ground Observations for Drought Characterization in Northwestern China

Guo

Nzabarinda

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

Long-term satellite-based precipitation estimates (LSPE) play a significant role in climatological studies like drought monitoring. In this study, three popular LSPEs (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), Rainfall Estimates from Rain Gauge and Satellite Observations (CHIRPS) and Multi-Source Weighted-Ensemble Precipitation (MSWEP)) were evaluated on a monthly scale using ground-based stations for capturing drought event characteristics over northwestern China from 1983 to 2013. To reflect dry or wet evolution, the Standardized Precipitation Index (SPI) was adopted, and the Run theory was used to identify drought events and their characteristics. The conventional statistical indices (relative bias (RB), correlation coefficient (CC), and root mean square error (RMSE)), as well as categorical indices (probability of detection (POD), false alarm ratio (FAR), and missing ratio (MISS)) are used to evaluate the capability of LSPEs in estimating precipitation and drought characteristics. We found that: (1) three LSPEs showed generally satisfactory performance in estimating precipitation and characterizing drought events. Although LSPEs have acceptable performance in identifying drought events with POD greater than 60%, they still have a high false alarm ratio (>27%) and a high missing ratio (>33%); (2) three LSPEs tended to overestimate drought severity, mainly because of an overestimation of drought duration; (3) the ability of CHIRPS to replicate the temporal evolution of precipitation and SPI values is limited; (4) in severe drought events, PERSIANN-CDR tends to overestimate precipitation, and drought severity, as well as drought area; (5) among the three LSPEs, MSWEP outperformed the other two in identifying drought events (POD > 66%) and characterizing drought features. Finally, we recommend MSWEP for drought monitoring studies due to its high accuracy in estimating drought characteristics over northwestern China. In drought monitoring applications, the overestimation of PERSIANN-CDR for drought peak value and area, as well as CHIRPS’s inferiority in capturing drought temporal evolution, must be considered.

show abstract

Section: Statistics Evaluation Metricsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of Three Long-Term Satellite-Based Precipitation Estimates against Ground Observations for Drought Characterization in Northwestern China

Guo

Nzabarinda

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Several SBP datasets have been developed after the success of the Tropical Rainfall Measuring Mission (TRMM). The newly developed SBP products such as Integrated Multi-satellite Retrievals for global precipitation measurement (GPM) (IMERG) (Huffman et al, 2015), Goddard profiling algorithm (GPROF) (Kummerow et al, 2015) and SM2RAIN-ASCAT (Brocca et al, 2019) showed impressive rainfall estimation capability over various regions (Suliman et al, 2020). However, SBP is an indirect estimation of precipitation, and the precision of SBP depends on the sensor used and the retrieval algorithm applied (Hsu et al, 1997).…”

Section: Introductionmentioning

confidence: 99%

Bias correction method of high-resolution satellite-based precipitation product for Peninsular Malaysia

Iqbal

Shahid

Ahmed

et al. 2022

Theor Appl Climatol

Self Cite

View full text Add to dashboard Cite

Satellite-based precipitation (SBP) is emerging as a reliable source for high-resolution rainfall estimates over the globe. However, uncertainty in SBP is still significant, limiting their use without evaluation and often without bias correction. The bias correction of SBP remained a challenge for atmospheric scientists. In this study, the performance of six SBPs, namely, SM2RAIN-ASCAT, IMERG, GsMap, CHIRPS, PERSIANN-CDS and PERSIANN-CSS in replicating observed daily rainfall at 364 stations over Peninsular Malaysia was evaluated. The bias of the most suitable SBP was corrected using a novel machine learning (ML)-based bias-correction method. The proposed bias-correction method consists of an ML classifier to correct the bias in estimating rainfall occurrence and an ML regression model to correct the amount of rainfall during rainfall events. The performance of different widely used ML algorithms for classification and regression were evaluated to select the suitable algorithms. IMERG showed better performance, showing a higher correlation coefficient (R 2 ) of 0.57 and Kling-Gupta Efficiency (KGE) of 0.5 compared to the other products. The performance of random forest (RF) was better than the knearest neighbourhood (KNN) for both classification and regression. RF classified the rainfall events with a skill score of 0.38 and estimated the rainfall amount of a rainfall event with the modified Index of Agreement (md) of 0.56. Comparison of IMERG and bias-corrected IMERG (BIMERG) revealed an average reduction in RMSE by 55% in simulating observed rainfall. The proposed bias correction method performed much better when compared with the conventional bias correction methods such as linear scaling and quantile regression. The BIMERG could reliably replicate the spatial distribution of heavy rainfall events, indicating its potential for hydro-climatic studies like flood and drought monitoring in the study area.

show abstract

“…The phenomenon of drought in semi-arid countries is generally analyzed by considering the series of rainfall events (Alvalá et al, 2019;Mugari et al, 2020;Ahmed Suliman et al, 2020 An analysis, which makes use the dry spell, particularly the extreme dry spell re ecting the variation of extreme drought condition, still needs to be further concerned and analyzed (Dunxian et al, 2016). This study uses the model by alternating wet/dry spell to analyze the drought according the variation of precipitation threshold.…”

Section: Introductionmentioning

confidence: 99%

Dry events according a precipitation threshold value in the Mediterranean climate of northern Tunisia

Mathlouthi¹,

Lebdi

2022

Preprint

View full text Add to dashboard Cite

Dry spells observed in Ichkeul basin Northern Tunisia using daily precipitation data were analyzed. Dry days were defined as having less than a threshold value of accumulated precipitation. Various values of the threshold were investigated. Analysis point dry spells occur randomly during the rainy season. The longest dry spells associated with various statistical recurrence periods are derived on the basis of the fitted Generalized Extreme Value (GEV) distributions. An extreme case (meteorological droughts) was analysed. From the drought return period analysis, the 1 September 1987 drought was found to be the most extreme with a 127-yr return period. The maximum number of seasonal dry events observed is inversely proportional to the threshold value. Longest observed in rainfall event duration is invariant to the rainfall threshold and displays 13 days. This study provides the foundation data for reducing Ichkeul’s vulnerability to future droughts, and investigating the causes of droughts.

show abstract

Evaluation of remotely sensed precipitation sources for drought assessment in Semi-Arid Iraq

Cited by 42 publications

References 56 publications

Assessment of Three Long-Term Satellite-Based Precipitation Estimates against Ground Observations for Drought Characterization in Northwestern China

Assessment of Three Long-Term Satellite-Based Precipitation Estimates against Ground Observations for Drought Characterization in Northwestern China

Bias correction method of high-resolution satellite-based precipitation product for Peninsular Malaysia

Dry events according a precipitation threshold value in the Mediterranean climate of northern Tunisia

Contact Info

Product

Resources

About