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Haowen Yue, Mekonnen Gebremichael, and Vahid Nourani

Abstract

Reliable weather forecasts are valuable in a number of applications, such as agriculture, hydropower, and weather-related disease outbreaks. Global weather forecasts are widely used, but detailed evaluation over specific regions is paramount for users and operational centers to enhance the usability of forecasts and improve their accuracy. This study presents evaluation of the Global Forecast System (GFS) medium-range (1–15 day) precipitation forecasts in the nine subbasins of the Nile basin using NASA’s Integrated Multisatellite Retrievals (IMERG) Final Run satellite–gauge merged rainfall observations. The GFS products are available at a temporal resolution of 3–6 h and a spatial resolution of 0.25°, and the version-15 products are available since 12 June 2019. GFS forecasts are evaluated at a temporal scale of 1–15 days, a spatial scale from 0.25° to all the way to the subbasin scale, and for a period of one year (15 June 2019–15 June 2020). The results show that performance of the 1-day lead daily basin-averaged GFS forecast performance, as measured through the modified Kling–Gupta efficiency (KGE), is poor (0 < KGE < 0.5) for most of the subbasins. The factors contributing to the low performance are 1) large overestimation bias in watersheds located in wet climate regimes in the northern hemispheres (Millennium watershed, Upper Atbara and Setit watershed, and Khashm El Gibra watershed), and 2) lower ability in capturing the temporal dynamics of watershed-averaged rainfall that have smaller watershed areas (Roseires at 14 110 km2 and Sennar at 13 895 km2). GFS has better bias for watersheds located in the dry parts of the Northern Hemisphere or wet parts of the Southern Hemisphere, and better ability in capturing the temporal dynamics of watershed-average rainfall for large watershed areas. IMERG Early has better bias than GFS forecast for the Millennium watershed but still comparable and worse bias for the Upper Atbara and Setit and Khashm El Gibra watersheds. The variation in the performance of the IMERG Early could be partly explained by the number of rain gauges used in the reference IMERG Final product, as 16 rain gauges were used for the Millennium watershed but only one rain gauge over each Upper Atbara and Setit and Khashm El Gibra watershed. A simple climatological bias correction of IMERG Early reduces in the bias in IMERG Early over most watersheds, but not all watersheds. We recommend exploring methods to increase the performance of GFS forecasts, including postprocessing techniques through the use of both near-real-time and research-version satellite rainfall products.

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Andrew M. Badger, Christa Peters-Lidard, and Dalia B. Kirschbaum

Abstract

A globally consistent ground validation method for remotely sensed precipitation products is crucial for building confidence in these products. This study develops a new methodology to validate the IMERG precipitation products through the use of SMAP soil moisture changes as a proxy for precipitation occurrence. Using a standard 2 × 2 contingency table method, preliminary results provide confidence in SMAP’s ability to be utilized as a validation tool for IMERG as results are comparable to previous validation studies. However, the method allows for an overestimate of false alarm frequency due to light precipitation events that can evaporate before the subsequent SMAP overpass and changes in overpass-to-overpass SMAP soil moisture that are within the range of SMAP uncertainty. To counter these issues, a 3 × 3 contingency table is used to reduce noise and extract more signal from the detection method. Through the use of this novel approach, the validation method produces a global mean POD of 0.64 and global mean FAR of 0.40, the first global-scale ground validation skill scores for the IMERG products. Advancing the method to validate precipitation quantity and the development of a real-time validation for the IMERG Early product are the crucial next developments.

Significance Statement

We wanted to see if there was a method in which remotely sensed precipitation observations could be validated at a near-global scale for land areas. Scientific literature is filled with studies that validate various precipitation datasets over local-to-regional scales, with very few extending beyond that domain. This study provides a robust first attempt at validating a global precipitation product at a global scale using changes in remotely sensed soil moisture as an independent proxy for precipitation presence/absence. While the method demonstrates that there is skill in using soil moisture as a tool to validate precipitation at the global scale, we find that there are still instances of a systemic bias for arid climate regimes. This method lays the groundwork for future studies to provide a comprehensive global validation in a globally consistent manner.

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Yawen Shao, Quan J. Wang, Andrew Schepen, Dongryeol Ryu, and Florian Pappenberger

Abstract

Climate trends have been observed over the recent decades in many parts of the world, but current global climate models (GCMs) for seasonal climate forecasting often fail to capture these trends. As a result, model forecasts may be biased above or below the trendline. In our previous research, we developed a trend-aware forecast postprocessing method to overcome this problem. The method was demonstrated to be effective for embedding observed trends into seasonal temperature forecasts. In this study, we further develop the method for postprocessing GCM seasonal precipitation forecasts. We introduce new formulation and evaluation features to cater for special characteristics of precipitation amounts, such as having a zero lower bound and highly positive skewness. We apply the improved method to calibrate ECMWF SEAS5 forecasts of seasonal precipitation for Australia. Our evaluation shows that the calibrated forecasts reproduce observed trends over the hindcast period of 36 years. In some regions where observed trends are statistically significant, forecast skill is greatly improved by embedding trends into the forecasts. In most regions, the calibrated forecasts outperform the raw forecasts in terms of bias, skill, and reliability. Wider applications of the new trend-aware postprocessing method are expected to boost user confidence in seasonal precipitation forecasts.

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Nishan Kumar Biswas and Faisal Hossain

Abstract

The limited amount of shared reservoir monitoring data around the world is insufficient to quantify the dynamic nature of reservoir operation with conventional ground-based methods. With the emergence of the Reservoir Assessment Tool (RAT) driven by a multitude of Earth-observing satellites and models, historical observation of reservoir operation spanning 35 years was made using open-source techniques. Trends in reservoir storage change were compared with trends of four critical hydrologic variables (precipitation, runoff, evaporation, and Palmer drought severity index) to understand the potential role of natural drivers in altering reservoir operating pattern. It was found that the reservoirs in Africa were losing active storage at a rate of more than 1% per year of total storage capacity. Smaller reservoirs (with a capacity of less than 0.5 km3) in Southeast Asia were found to experience a sharp gain in storage of 0.5%–1% per year of total storage capacity. Storage change trends of large reservoirs with multiple years of residence time that are designed for strategic water supply needs and drought control were found to be less affected by precipitation trends and influenced more by drought and evaporation trends. Over Africa, most reservoir storage change trends were dictated by evaporation trends, while South Asian reservoirs appear to have their storage change influenced by drought and evaporation trends. Finally, findings suggest that operation of newer reservoirs is more sensitive to long-term hydrological trends and the regulated surface water variability that is controlled by older dams in the upstream.

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Suleiman Mostamandi, Evgeniya Predybaylo, Sergey Osipov, Olga Zolina, Sergey Gulev, Sagar Parajuli, and Georgiy Stenchikov

Abstract

The Red Sea (RS) has a high evaporation rate, exceeding 2 m of water per year. The water vapor is transported from the shorelines by sea breezes as far as 200 km landward. Relative humidity in the vicinity of the RS exceeds 80% in summer. Nevertheless, precipitation is scarce in most of the Arabian RS coastal plain. In this work we use the Weather Research and Forecasting (WRF) regional model to assess how deliberate changes (geoengineering) in the surface albedo or conversion of bare land to wide-leaf forests over a vast coastal plain region affect precipitation over the Arabian RS coast. Our simulations show that geoengineering of land surface characteristics perturbs coastal circulation; alters temperature, moisture, and momentum exchange between the land surface and atmosphere; and changes the breeze intensity, cloud cover, and eventually the amount of precipitation. We find that extended afforestation and increased surface albedo are not effective in triggering rainfall over the RS coastal plains. Conversely, decreasing surface albedo to 0.2, assuming installation of solar panels over the coastal plains, increases surface air temperature by 1–2 K, strengthens horizontal surface temperature differences between sea and land, intensifies breezes, increases water vapor mixing ratio in the boundary layer above 3 km by about 0.5 g kg−1, enhances vertical mixing within the planetary boundary layer, and generates 1.5 Gt of extra rainwater, equivalent to the annual consumption of five million people. Thus, this form of regional land surface geoengineering, along with advanced methods of collection and underground storage of freshwater, provides a feasible solution to mitigation of the existing water crisis in the arid coastal regions.

Open access
Xiaokang Wang, Renjun Zhou, Yi Deng, Chunguang Cui, Yang Hu, Jingyu Wang, and Hua Liu

Abstract

Observational evidence from a heavy precipitation event of the 2020 extreme mei-yu season is presented here to reveal a symbiotic relationship between mei-yu rainfall and the morphology of the mei-yu front. The two influence each other through dynamical and thermodynamic feedbacks and evolve in a coherent way to generate cyclic behaviors. Specifically, an intense and band-shaped mei-yu front leads to symmetrical instability in the lower atmospheric layer and convective instability in the middle atmospheric layer, forming a rainband along the front. The mei-yu front and its associated instability subsequently weaken as a result of rainfall, and the front is bent by the process of tilting frontolysis. Deep convective instability in the middle and lower layers develops in the warm, humid prefrontal area, and triggers isolated heavy rainfall replacing the original rainband south of the bent front. This warm sector precipitation then strengthens the front through tilting and diabatic heating frontogenesis. A stronger front recovers its initial band shape, and the associated rainfall also resumes the form of a rainband along the front. Analyses of potential energy associated with instability, water vapor convergence, and cross-frontal circulation are carried out to illustrate key processes of this mei-yu front–rainfall cycle. The implications of this symbiotic relationship for simulating and predicting extreme rainfall associated with mei-yu fronts are presented.

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Huawu Wu, Congsheng Fu, Cicheng Zhang, Jianming Zhang, Zhongwang Wei, and Xinping Zhang

Abstract

Long-term continuous monitoring of precipitation isotopes has great potential to advance our understanding of hydrometeorological processes that determine stable isotope variability in the monsoon regions. This study presents 4-yr daily precipitation isotopes from Yungui Plateau in southwestern China that are influenced by Indian summer monsoon and East Asian monsoon. The local meteoric water line (LMWL; δ 2H = 8.12δ 18O + 11.2) was first established at the Tengchong (TC) site, which was close to the global meteoric water line (GMWL; δ 2H = 8δ 18O + 10), indicating little secondary subcloud evaporation in the falling rain. Precipitation δ 18O values exhibited significant inverse relationships with precipitation amount (r = −0.42), air temperature (r = −0.43), and relative humidity (r = −0.41) with lower correlation coefficients throughout the entire period, which indicated that precipitation isotopic variability in TC could not be well explained by the local meteorological factors but influenced by other combined factors of regional precipitation amount and upstream rainout. Precipitation δ 18O values showed a clear V-shaped trend throughout the observation period, characterized by higher δ 18O values during the premonsoon period whereas lower values during the postmonsoon period. This seasonal variation of precipitation δ 18O values was associated with the seasonal movement of the intertropical convergence zone and seasonal changes in moisture transport. Combined with backward trajectory analysis, precipitation δ 18O values were estimated by a Rayleigh distillation model showing that upstream rainout processes from the Bay of Bengal (BoB) toward land (Myanmar) and recycling moisture over land were key factors affecting the isotopic compositions of the TC precipitation. These findings could enhance our understanding of atmospheric dynamics and moisture source in the monsoon regions and will potentially facilitate the interpretation of numerous isotopic proxy records from this region.

SIGNIFICANCE STATEMENT

The variability of the summer monsoon and its onset, duration, and failure directly determine the strong rainfall and drought in a given region and have great impacts on regional societies and agriculture. To better understand this variability, this study presented a 4-yr daily dataset of precipitation isotopes on the Yungui Plateau of southwestern China to explore atmospheric processes and moisture sources that drive isotopic variability in this region. Precipitation δ 18O exhibited remarkably seasonal variability, with higher values in premonsoon period and lower values in the postmonsoon period. During the Indian summer monsoon period, moisture sources primarily originated from the BoB toward the TC site, experiencing rainout processes and local moisture recycling over land using a Rayleigh fractionation model. These findings shed new light on the temporal variations of precipitation stable isotopes and facilitate our understanding of hydrological cycle in the monsoon regions.

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Maofeng Liu, James A. Smith, Long Yang, and Gabriel A. Vecchi

Abstract

The climatology of tropical cyclone flooding in the Carolinas is analyzed through annual flood peak observations from 411 U.S. Geological Survey (USGS) stream gauging stations. Tropical cyclones (TCs) account for 28% of the top 10 annual flood peaks, 55% of record floods, and 91% of floods with peak magnitudes at least 5 times greater than the 10-yr floods, highlighting the prominent role of TCs for flood extremes in the Carolinas. Of all TC-related flood events, the top 10 storms account for nearly 1/3 of annual flood peaks and more than 2/3 of record floods, reflecting the dominant role of a small number of storms in determining the upper tail of flood peak distributions. Analyses of the 10 storms highlight both common elements and diversity in storm properties that are responsible for flood peaks. Extratropical transition and orographic enhancement are important elements of extreme TC flooding in the Carolinas. Analyses of the Great Flood of 1916 highlight the flood peak of 3115 m3 s−1 in French Broad River at Asheville, 2.6 times greater than the second-largest peak from a record of 124 years. We also examine the hydroclimatology, hydrometeorology, and hydrology of flooding from Hurricanes Matthew (2016) and Florence (2018). Results point to contrasting storm properties for the two events, including tracks as well as rainfall distribution and associated physical mechanisms. Climatological analyses of vertically integrated water vapor transport (IVT) highlight the critical role of anomalous moisture transport from the Atlantic Ocean in producing extreme rainfall and flooding over the Carolinas.

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Shiori Sugimoto, Kenichi Ueno, Hatsuki Fujinami, Tomoe Nasuno, Tomonori Sato, and Hiroshi G. Takahashi

Abstract

A numerical experiment with a 2-km resolution was conducted using the Weather Research and Forecasting (WRF) Model to investigate physical processes driving nocturnal precipitation over the Himalayas during the mature monsoon seasons between 2003 and 2010. The WRF Model simulations of increases in precipitation twice a day, one in the afternoon and another around midnight, over the Himalayan slopes, and of the single nocturnal peak over the Himalayan foothills were reasonably accurate. To understand the synoptic-scale moisture transport and its local-scale convergence generating the nocturnal precipitation, composite analyses were conducted using the reanalysis dataset and model outputs. In the synoptic scale, moisture transport associated with the westward propagation of low pressure systems was found when nocturnal precipitation dominated over the Himalayan slopes. In contrast, moisture was directly provided from the synoptic-scale monsoon westerlies for nocturnal precipitation over the foothills. The model outputs suggested that precipitation occurred on the mountain ridges in the Himalayas during the afternoon and expanded horizontally toward lower-elevation areas through the night. During the nighttime, the downslope wind was caused by radiative cooling at the surface and was intensified by evaporative cooling by hydrometeors in the near-surface layer. As a result, convergence between the downslope wind and the synoptic-scale flow promoted nocturnal precipitation over the Himalayas and to the south, as well as the moisture convergence by orography and/or synoptic-scale circulation patterns. The nocturnal precipitation over the Himalayas was not simulated well when we used the coarse topographic resolution and the smaller number of vertical layers.

Open access
Peter E. Goble, Rebecca A. Bolinger, and Russ S. Schumacher

Abstract

Agricultural droughts afflicting the contiguous United States (CONUS) are serious and costly natural hazards. Widespread damage to a single cash crop may be crippling to rural communities that produce it. While drought is insidious in nature, drought indices derived from meteorological data and drought impact reports both provide essential guidance to decision-makers about the location and intensity of developing and ongoing droughts. However, response to dry meteorological conditions is not consistent from one crop type to the next, making crop-specific drought appraisal difficult using weather data alone. Additionally, drought impact reports are often subjective, latent, or both. To rectify this, we developed drought indices using meteorological data, and phenological information for the row crops most commonly grown over CONUS: corn, soybeans, and winter wheat. These are referred to as crop-specific standardized precipitation–evapotranspiration indices (CSPEIs). CSPEIs correlate more closely with end-of-season yields than traditional meteorological indicators for the eastern two thirds of CONUS for corn, and offer an advantage in predicting winter wheat yields for the High Plains. CSPEIs do not always explain a higher fraction of variance than traditional meteorological indicators. In such cases, results provide insight on which meteorological indicators to use to most effectively supplement impacts information.

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