Showing papers in "Journal of Hydrometeorology in 2017"

Reprocessed, Bias-Corrected CMORPH Global High-Resolution Precipitation Estimates from 1998

Abstract: The Climate Prediction Center (CPC) morphing technique (CMORPH) satellite precipitation estimates are reprocessed and bias corrected on an 8 km × 8 km grid over the globe (60°S–60°N) and in a 30-min temporal resolution for an 18-yr period from January 1998 to the present to form a climate data record (CDR) of high-resolution global precipitation analysis. First, the purely satellite-based CMORPH precipitation estimates (raw CMORPH) are reprocessed. The integration algorithm is fixed and the input level 2 passive microwave (PMW) retrievals of instantaneous precipitation rates are from identical versions throughout the entire data period. Bias correction is then performed for the raw CMORPH through probability density function (PDF) matching against the CPC daily gauge analysis over land and through adjustment against the Global Precipitation Climatology Project (GPCP) pentad merged analysis of precipitation over ocean. The reprocessed, bias-corrected CMORPH exhibits improved performance in represen...

Assessment of the SMAP Level-4 surface and root-zone soil moisture product using in situ measurements

Abstract: The Soil Moisture Active Passive (SMAP) mission Level-4 Surface and Root-Zone Soil Moisture (L4_SM) data product is generated by assimilating SMAP L-band brightness temperature observations into the NASA Catchment land surface model. The L4_SM product is available from 31 March 2015 to present (within 3 days from real time) and provides 3-hourly, global, 9-km resolution estimates of surface (0–5 cm) and root-zone (0–100 cm) soil moisture and land surface conditions. This study presents an overview of the L4_SM algorithm, validation approach, and product assessment versus in situ measurements. Core validation sites provide spatially averaged surface (root zone) soil moisture measurements for 43 (17) “reference pixels” at 9- and 36-km gridcell scales located in 17 (7) distinct watersheds. Sparse networks provide point-scale measurements of surface (root zone) soil moisture at 406 (311) locations. Core validation site results indicate that the L4_SM product meets its soil moisture accuracy requirement, specified as an unbiased RMSE (ubRMSE, or standard deviation of the error) of 0.04 m3 m−3 or better. The ubRMSE for L4_SM surface (root zone) soil moisture is 0.038 m3 m−3 (0.030 m3 m−3) at the 9-km scale and 0.035 m3 m−3 (0.026 m3 m−3) at the 36-km scale. The L4_SM estimates improve (significantly at the 5% level for surface soil moisture) over model-only estimates, which do not benefit from the assimilation of SMAP brightness temperature observations and have a 9-km surface (root zone) ubRMSE of 0.042 m3 m−3 (0.032 m3 m−3). Time series correlations exhibit similar relative performance. The sparse network results corroborate these findings over a greater variety of climate and land cover conditions.

A Global Gridded Dataset of GRACE Drought Severity Index for 2002–14: Comparison with PDSI and SPEI and a Case Study of the Australia Millennium Drought

Abstract: A new monthly global drought severity index (DSI) dataset developed from satellite-observed time-variable terrestrial water storage changes from the Gravity Recovery and Climate Experiment (GRACE) is presented. The GRACE-DSI record spans from 2002 to 2014 and will be extended with the ongoing GRACE and scheduled GRACE Follow-On missions. The GRACE-DSI captures major global drought events during the past decade and shows overall favorable spatiotemporal agreement with other commonly used drought metrics, including the Palmer drought severity index (PDSI) and the standardized precipitation evapotranspiration index (SPEI). The assets of the GRACE-DSI are 1) that it is based solely on satellite gravimetric observations and thus provides globally consistent drought monitoring, particularly where sparse ground observations (especially precipitation) constrain the use of traditional model-based monitoring methods; 2) that it has a large footprint (~350 km), so it is suitable for assessing regional- and g...

Evaluation of Integrated Multisatellite Retrievals for GPM (IMERG) over Southern Canada against Ground Precipitation Observations: A Preliminary Assessment

Abstract: The Global Precipitation Measurement (GPM) mission offers new opportunities for modeling a range of physical/hydrological processes at higher resolutions, especially for remote river systems where the hydrometeorological monitoring network is sparse and weather radar is not readily available. In this study, the recently released Integrated Multisatellite Retrievals for GPM [version 03 (V03) IMERG Final Run] product with high spatiotemporal resolution of 0.1° and 30 min is evaluated against ground-based reference measurements (at the 6-hourly, daily, and monthly time scales) over different terrestrial ecozones of southern Canada within a 23-month period from 12 March 2014 to 31 January 2016. While IMERG and ground-based observations show similar regional variations of mean daily precipitation, IMERG tends to overestimate higher monthly precipitation amounts over the Pacific Maritime ecozone. Results from using continuous as well as categorical skill metrics reveal that IMERG shows more satisfactory...

Performance of IMERG as a Function of Spatiotemporal Scale

Abstract: The Integrated Multi-satellitE Retrievals for GPM (IMERG), a global high-resolution gridded precipitation data set, will enable a wide range of applications, ranging from studies on precipitation characteristics to applications in hydrology to evaluation of weather and climate models. These applications focus on different spatial and temporal scale and thus average the precipitation estimates to coarser resolutions. Such a modification of scale will impact the reliability of IMERG. In this study, the performance of the Final run of MERG is evaluated against ground-based measurements as a function of increasing spatial resolution (from 0.1° to 2.5 ) and accumulation periods (from 0.5 h to 24 h) over a region in the southeastern US. For ground reference, a product derived from the Multi-Radar/Multi-Sensor suite, a radar- and gauge-based operational precipitation dataset, is used. The TRMM Multi satellite Precipitation Analysis (TMPA) is also included as a benchmark. In general, both IMERG and TMPA improve when scaled up to larger areas and longer time periods, with better identification of rain occurrences and consistent improvements in systematic and random errors of rain rates. Between the two satellite estimates, IMERG is slightly better than TMPA most of the time. These results will inform users on the reliability of IMERG over the scales relevant to their studies.

Intermittency in Precipitation: Duration, Frequency, Intensity, and Amounts Using Hourly Data

Abstract: Intermittency is a core characteristic of precipitation, not well described by data and very poorly modeled. Detailed analyses are made of near-global gridded (about 1°) hourly or 3-hourly precipitation rates from two updated observational datasets [3-hourly TRMM 3B42, version 7, and hourly CMORPH, version 1.0, bias corrected (CRT)] and from special runs of CESM from January 1998 to December 2013 to obtain hourly values. The analyses explore the intermittency of precipitation: the frequency, intensity, duration, and amounts. A comparison is made for all products using several metrics with a focus on the duration of events, and a new metric is proposed based on the ratio of the frequency of precipitation at certain rates (0.2–2 mm h−1) for hourly versus 3-hourly versus daily data. For all seasons and rain rates, TRMM values are similar in pattern to CMORPH, but durations are about 80%–85%. It is mainly over land in the monsoons that CMORPH exceeds TRMM rain durations. Observed duration of precipita...

Global Assessment of the SMAP Level-4 Surface and Root-Zone Soil Moisture Product Using Assimilation Diagnostics

Abstract: The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0–5 cm) and root-zone (0–100 cm) soil moisture and related land surface variables from 31 March 2015 to present with ~2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O − F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of ~0.37 K for the O − F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O − F residuals (under ~3 K), the soil moisture increments (under ~0.01 m3 m−3), and the sur...

Dropsonde Observations of Total Integrated Water Vapor Transport within North Pacific Atmospheric Rivers

Abstract: Aircraft dropsonde observations provide the most comprehensive measurements to date of horizontal water vapor transport in atmospheric rivers (ARs). The CalWater experiment recently more than tripled the number of ARs probed with the required measurements. This study uses vertical profiles of water vapor, wind, and pressure obtained from 304 dropsondes across 21 ARs. On average, total water vapor transport (TIVT) in an AR was 4.7 × 108 ± 2 × 108 kg s−1. This magnitude is 2.6 times larger than the average discharge of liquid water from the Amazon River. The mean AR width was 890 ± 270 km. Subtropical ARs contained larger integrated water vapor (IWV) but weaker winds than midlatitude ARs, although average TIVTs were nearly the same. Mean TIVTs calculated by defining the lateral “edges” of ARs using an IVT threshold versus an IWV threshold produced results that differed by less than 10% across all cases, but did vary between the midlatitudes and subtropical regions.

Validation of IMERG Precipitation in Africa

Abstract: Understanding of hydroclimatic processes in Africa has been hindered by the lack of in situ precipitation measurements. Satellite-based observations, in particular, the TRMM Multisatellite Precipitation Analysis (TMPA) have been pivotal to filling this void. The recently released Integrated Multisatellite Retrievals for GPM (IMERG) project aims to continue the legacy of its predecessor, TMPA, and provide higher-resolution data. Here, IMERG-V04A precipitation data are validated using in situ observations from the Trans-African Hydro-Meteorological Observatory (TAHMO) project. Various evaluation measures are examined over a select number of stations in West and East Africa. In addition, continent-wide comparisons are made between IMERG and TMPA. The results show that the performance of the satellite-based products varies by season, region, and the evaluation statistics. The precipitation diurnal cycle is relatively better captured by IMERG than TMPA. Both products exhibit a better agreement with gauge data in East Africa and humid West Africa than in the southern Sahel. However, a clear advantage for IMERG is not apparent in detecting the annual cycle. Although all gridded products used here reasonably capture the annual cycle, some differences are evident during the short rains in East Africa. Direct comparison between IMERG and TMPA over the entire continent reveals that the similarity between the two products is also regionally heterogeneous. Except for Zimbabwe and Madagascar, where both satellite-based observations present a good agreement, the two products generally have their largest differences over mountainous regions. IMERG seems to have achieved a reduction in the positive bias evident in TMPA over Lake Victoria.

Total and extreme precipitation changes over the northeastern united states.

Abstract: The Northeastern United States has experienced a large increase in precipitation over recent decades. Annual and seasonal changes of total and extreme precipitation from station observations in the Northeast are assessed over multiple time periods spanning 1901-2014. Spatially averaged, both annual total and extreme precipitation across the Northeast have increased significantly since 1901, with changepoints occurring in 2002 and 1996, respectively. Annual extreme precipitation has experienced a larger increase than total precipitation; extreme precipitation from 1996-2014 was 53% higher than from 1901-1995. Spatially, coastal areas received more total and extreme precipitation on average, but increases across the changepoints are distributed fairly uniformly across the domain. Increases in annual total precipitation across the 2002 changepoint have been driven by significant total precipitation increases in fall and summer, while increases in annual extreme precipitation across the 1996 changepoint have been driven by significant extreme precipitation increases in fall and spring. The ability of gridded observed and reanalysis precipitation data to reproduce station observations was also evaluated. Gridded observations perform well in reproducing averages and trends of annual and seasonal total precipitation, but extreme precipitation trends show significantly different spatial and domain-averaged trends than station data. North American Regional Reanalysis generally underestimates annual and seasonal total and extreme precipitation means and trends relative to station observations, and also shows substantial differences in the spatial pattern of total and extreme precipitation trends within the Northeast.

An Improved Dual-Polarization Radar Rainfall Algorithm (DROPS2.0): Application in NASA IFloodS Field Campaign

Abstract: Compared to traditional single-polarization radar, dual-polarization radar has a number of advantages for quantitative precipitation estimation because more information about the drop size distribution and hydrometeor type can be gleaned. In this paper, an improved dual-polarization rainfall methodology is proposed, which is driven by a region-based hydrometeor classification mechanism. The objective of this study is to incorporate the spatial coherence and self-aggregation of dual-polarization observables in hydrometeor classification and to produce robust rainfall estimates for operational applications. The S-band dual-polarization data collected from the NASA Polarimetric (NPOL) radar during the GPM Iowa Flood Studies (IFloodS) ground validation field campaign are used to demonstrate and evaluate the proposed rainfall algorithm. Results show that the improved rainfall method provides better performance than a few single- and dual-polarization algorithms in previous studies. This paper also inve...

Benchmarking of a Physically Based Hydrologic Model

Abstract: The concepts of model benchmarking, model agility, and large-sample hydrology are becoming more prevalent in hydrologic and land surface modeling. As modeling systems become more sophisticated, these concepts have the ability to help improve modeling capabilities and understanding. In this paper, their utility is demonstrated with an application of the physically based Variable Infiltration Capacity model (VIC). The authors implement VIC for a sample of 531 basins across the contiguous United States, incrementally increase model agility, and perform comparisons to a benchmark. The use of a large-sample set allows for statistically robust comparisons and subcategorization across hydroclimate conditions. Our benchmark is a calibrated, time-stepping, conceptual hydrologic model. This model is constrained by physical relationships such as the water balance, and it complements purely statistical benchmarks due to the increased physical realism and permits physically motivated benchmarking using metrics...

Characterizing Drought in India Using GRACE Observations of Terrestrial Water Storage Deficit

Abstract: Frequent recurrences of drought in India have had major societal, economical, and environmental impacts. While region-specific assessments are abundant, exhaustive appraisal over large spatial scales has been insubstantial. Here a new drought index called Water Storage Deficit Index (WSDI) is devised and analyzed for holistic representation of drought. The crux of the method is the employment of terrestrial water storage (TWS) variations from Gravity Recovery and Climate Experiment (GRACE) for quantification of drought intensity and severity. Drought events in recent times are well identified and quantified using the approach over four homogenous rainfall regions of India over the period from April 2002 to April 2015. Among the four regions, the highest peak deficit of −158.00 mm is observed in January 2015 over central India. While the drought of 2002–04 is prominent in peninsular and west-central India, the drought of 2009–10 and 2012–13 is conspicuous in almost all four regions of India. The lo...

Intercomparisons of Rainfall Estimates from TRMM and GPM Multisatellite Products over the Upper Mekong River Basin

Abstract: The aim of this study is to evaluate the accuracy of daily rainfall estimates based on the GPM level-3 final product derived from the IMERG algorithm (abbreviated as IMERG) and TRMM 3B42, version 7 (abbreviated as 3B42), in the upper Mekong River basin, a mountainous region in southwestern China. High-density rain gauges provide exceptional resources for ground validation of satellite rainfall estimates over this region. The performance of the two satellite rainfall products is evaluated during two rainy seasons (May–October) over the period 2014–15, as well as their applications in hydrological simulations. Results indicate that 1) IMERG systematically reduces the bias value in rainfall estimates at the gridbox scale and presents a greater ability to capture rainfall variability at the local domain scale compared with 3B42; 2) IMERG improves the ability to capture rain events with moderate intensities and presents higher capability in detecting occurrences of extreme rain events, but significantl...

Recent Evidence of Large-Scale Receding Snow Water Equivalents in the European Alps

Abstract: Snow plays a critical role in the water cycle of many mountain regions and heavily populated areas downstream. In this study, changes of snow water equivalent (SWE) time series from long-term stations in five Alpine countries are analyzed. The sites are located between 500 and 3000 m above mean sea level, and the analysis is mainly based on measurement series from 1 February (winter) and 1 April (spring). The investigation was performed over different time periods, including the last six decades. The large majority of the SWE time series demonstrate a reduction in snow mass, which is more pronounced for spring than for winter. The observed SWE decrease is independent of latitude or longitude, despite the different climate regions in the Alpine domain. In contrast to measurement series from other mountain ranges, even the highest sites revealed a decline in spring SWE. A comparison with a 100-yr mass balance series from a glacier in the central Alps demonstrates that the peak SWEs have been on a re...

How Does the Evaluation of the GPM IMERG Rainfall Product Depend on Gauge Density and Rainfall Intensity

Abstract: This study investigates the dependency of the evaluation of the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) rainfall product on the gauge density of a ground-based rain gauge network as well as rainfall intensity over five subregions in mainland China. High-density rain gauges (1.5 gauges per 100 km2) provide exceptional resources for ground validation of satellite rainfall estimates over this region. Eight different gauge networks were derived with contrasting gauge densities ranging from 0.04 to 4 gauges per 100 km2. The evaluation focuses on two warm seasons (April–October) during 2014 and 2015. The results show a strong dependency of the evaluation metrics for the IMERG rainfall product on gauge density and rainfall intensity. A dense rain gauge network tends to provide better evaluation metrics, which implies that previous evaluations of the IMERG rainfall product based on a relatively low-density gauge network might have underestimated its performance. T...

The Influence of Atmospheric Rivers over the South Atlantic on Winter Rainfall in South Africa

Abstract: A climatology of atmospheric rivers (ARs) impinging on the west coast of South Africa (29°–34.5°S) during the austral winter months (April–September) was developed for the period 1979–2014 using an automated detection algorithm and two reanalysis products as input. The two products show relatively good agreement, with 10–15 persistent ARs (lasting 18 h or longer) occurring on average per winter and nearly two-thirds of these systems occurring poleward of 35°S. The relationship between persistent AR activity and winter rainfall is demonstrated using South African Weather Service rainfall data. Most stations positioned in areas of high topography contained the highest percentage of rainfall contributed by persistent ARs, whereas stations downwind, to the east of the major topographic barriers, had the lowest contributions. Extreme rainfall days in the region are also ranked by their magnitude and spatial extent. The results suggest that although persistent ARs are important contributors to heavy rai...

Verification of land-atmosphere coupling in forecast models, reanalyses and land surface models using flux site observations.

Abstract: We confront four model systems in three configurations (LSM, LSM+GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly under-represent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling), and may over-represent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally under-represent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Our analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally-distributed observational monitoring.

An Intercomparison between Reanalysis and Dropsonde Observations of the Total Water Vapor Transport in Individual Atmospheric Rivers

Abstract: A recent study presented nearly two decades of airborne atmospheric river (AR) observations and concluded that, on average, an individual AR transports ~5 × 108 kg s−1 of water vapor. The study here compares those cases to ARs independently identified in reanalyses based on a refined algorithm that can detect less well-structured ARs, with the dual-purpose of validating reanalysis ARs against observations and evaluating dropsonde representativeness relative to reanalyses. The first comparison is based on 21 dropsonde-observed ARs in the northeastern Pacific and those closely matched, but not required to be exactly collocated, in ERA-Interim (MERRA-2), which indicates a mean error of −2% (−8%) in AR width and +3% (−1%) in total integrated water vapor transport (TIVT) and supports the effectiveness of the AR detection algorithm applied to the reanalyses. The second comparison is between the 21 dropsonde ARs and ~6000 ARs detected in ERA-Interim (MERRA-2) over the same domain, which indicates a mean ...

Mapping Flash Flood Severity in the United States

Abstract: Flash floods, a subset of floods, are a particularly damaging natural hazard worldwide because of their multidisciplinary nature, difficulty in forecasting, and fast onset that limits emergency responses. In this study, a new variable called “flashiness” is introduced as a measure of flood severity. This work utilizes a representative and long archive of flooding events spanning 78 years to map flash flood severity, as quantified by the flashiness variable. Flood severity is then modeled as a function of a large number of geomorphological and climatological variables, which is then used to extend and regionalize the flashiness variable from gauged basins to a high-resolution grid covering the conterminous United States. Six flash flood “hotspots” are identified and additional analysis is presented on the seasonality of flash flooding. The findings from this study are then compared to other related datasets in the United States, including National Weather Service storm reports and a historical floo...

A global dynamic long-term inundation extent dataset at high spatial resolution derived through downscaling of satellite observations

Abstract: A new procedure is introduced to downscale low-spatial-resolution inundation extents from Global Inundation Extent from Multi-Satellites (GIEMS) to a 3-arc-s (90 m) dataset (known as GIEMS-D3). The methodology is based on topography and hydrography information from the HydroSHEDS database. A new floodability index is introduced and an innovative smoothing procedure is developed to ensure a smooth transition, in the high-resolution maps, between the low-resolution boxes from GIEMS. Topography information is pertinent for natural hydrology environments controlled by elevation but is more limited in human-modified basins. However, the proposed downscaling approach is compatible with forthcoming fusion of other, more pertinent satellite information in these difficult regions. The resulting GIEMS-D3 database is the only high-spatial-resolution inundation database available globally at a monthly time scale over the 1993-2007 period. GIEMS-D3 is assessed by analyzing its spatial and temporal variability and evaluated by comparisons to other independent satellite observations from visible (Google Earth and Landsat), infrared (MODIS), and active microwave (synthetic aperture radar).

Comparison of Methods to Estimate Snow Water Equivalent at the Mountain Range Scale: A Case Study of the California Sierra Nevada

Abstract: Despite the importance of snow in global water and energy budgets, estimates of global mountain snow water equivalent (SWE) are not well constrained. Two approaches for estimating total range-wide SWE over Sierra Nevada, California, are assessed: 1) global/hemispherical models and remote sensing and models available for continental United States (CONUS) plus southern Canada (CONUS+) available to the scientific community and 2) regional climate model simulations via the Weather Research and Forecasting (WRF) Model run at 3, 9, and 27 km. As no truth dataset provides total mountain range SWE, these two approaches are compared to a “reference” SWE consisting of three published, independent datasets that utilize/validate against in situ SWE measurements. Model outputs are compared with the reference datasets for three water years: 2005 (high snow accumulation), 2009 (average), and 2014 (low). There is a distinctive difference between the reference/WRF datasets and the global/CONUS+ daily estimates of ...

A Comparison between the GPM Dual-Frequency Precipitation Radar and Ground-Based Radar Precipitation Rate Estimates in the Swiss Alps and Plateau

Abstract: The Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar (DPR) provides a unique set of three-dimensional radar precipitation estimates across much of the globe. Both terrain and climatic conditions can have a strong influence on the reliability of these estimates. Switzerland provides an ideal testbed to evaluate the performance of the DPR in complex terrain: it consists of a mixture of very complex terrain (the Alps) and the far flatter Swiss Plateau. It is also well instrumented, covered with a dense gauge network as well as a network of four dual-polarization C-band weather radars, with the same instrument network used in both the Plateau and the Alps. Here an evaluation of the GPM DPR rainfall rate products against the MeteoSwiss radar rainfall rate product for the first two years of the GPM DPR’s operation is presented. Errors in both detection and estimation are considered, broken down by terrain complexity, season, precipitation phase, precipitation type, and p...

Comparative Ground Validation of IMERG and TMPA at Variable Spatiotemporal Scales in the Tropical Andes

Abstract: An initial ground validation of the Integrated Multisatellite Retrievals for GPM (IMERG) Day-1 product from March 2014 to August 2015 is presented for the tropical Andes. IMERG was evaluated along with the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) against 302 quality-controlled rain gauges across Ecuador and Peru. Detection, quantitative estimation statistics, and probability distribution functions are calculated at different spatial (0.1°, 0.25°) and temporal (1 h, 3 h, daily) scales. Precipitation products are analyzed for hydrometeorologically distinct subregions. Results show that IMERG has a superior detection and quantitative rainfall intensity estimation ability than TMPA, particularly in the high Andes. Despite slightly weaker agreement of mean rainfall fields, IMERG shows better characterization of gauge observations when separating rainfall detection and rainfall rate estimation. At corresponding space–time scales, IMERG shows better estimati...

Quantifying the Snowfall Detection Performance of the GPM Microwave Imager Channels over Land

Abstract: This study uses Global Precipitation Measurement (GPM) Microwave Imager (GMI) and Ka-precipitation radar observations to quantify the snowfall detection performance for different channel (frequency) combinations. Results showed that the low-frequency-channel set contains limited snow detection information with a 0.34 probability of detection (POD). Much better performance is evident using the high-frequency channels (i.e., POD = 0.74). In addition, if only one high-frequency channel is allowed to be added to the low-frequency-channel set, adding the 183 ± 3 GHz channel presents the largest POD improvement (from 0.34 to 0.50). However, this does not imply that the water vapor is the key information for snowfall detection. Only using the high-frequency water vapor channels showed poor snowfall detection with POD at 0.13. Further analysis of all 8191 possible GMI channel combinations showed that the 166-GHz channels are indispensable for any channel combination with POD greater than 0.70. This sugges...

Comparison and Assessment of Three Advanced Land Surface Models in Simulating Terrestrial Water Storage Components over the United States

Abstract: To prepare for the next-generation North American Land Data Assimilation System (NLDAS), three advanced land surface models [LSMs; i.e., Community Land Model, version 4.0 (CLM4.0); Noah LSM with multiphysics options (Noah-MP); and Catchment LSM-Fortuna 2.5 (CLSM-F2.5)] were run for the 1979–2014 period within the NLDAS-based framework. Unlike the LSMs currently executing in the operational NLDAS, these three advanced LSMs each include a groundwater component. In this study, the model simulations of monthly terrestrial water storage anomaly (TWSA) and its individual water storage components are evaluated against satellite-based and in situ observations, as well as against reference reanalysis products, at basinwide and statewide scales. The quality of these TWSA simulations will contribute to determining the suitability of these models for the next phase of the NLDAS. Overall, it is found that all three models are able to reasonably capture the monthly and interannual variability and magnitudes of ...

Soil Moisture Drought Monitoring and Forecasting Using Satellite and Climate Model Data over Southwestern China

Abstract: In this paper, an experimental soil moisture drought monitoring and seasonal forecasting framework based on the Variable Infiltration Capacity model (VIC) over southwestern China (SW) is presented. Satellite precipitation data are used to force VIC for a near-real-time estimate of land surface hydrologic conditions. Initialized with satellite-aided monitoring (MONIT), the climate model (CFSv2)-based forecast (MONIT+CFSv2) and ensemble streamflow prediction (ESP)-based forecast (MONIT+ESP) are both performed. One dry season drought and one wet season drought are employed to test the ability of this framework in terms of real-time tracking and predicting the evolution of soil moisture (SM) drought, respectively. The results show that the skillful CFSv2 climate forecasts (CFs) are only found at the first month. The satellite-aided monitoring is able to provide a reasonable estimate of forecast initial conditions (ICs) in real-time mode. In the presented cases, MONIT+CFSv2 forecast exhibits comparable...

Bias Correction of Climate Modeled Temperature and Precipitation Using Artificial Neural Networks

Abstract: Climate studies and effective environmental management require unbiased climate datasets. This study develops a new bias correction approach using a three-layer feedforward neural network to reduce the biases of climate variables (temperature and precipitation) over northern South America. Air and skin temperature, specific humidity, and net longwave and shortwave radiation are used as inputs to the network for bias correction of 6-hourly temperature. Inputs to the network for bias correction of monthly precipitation are precipitation at lag 0, 1, 2, and 3 months, and also the standard deviation of precipitation from 3 × 3 neighbors around the pixel of interest. The climate model data are provided by the Community Climate System Model, version 3 (CCSM3). Results show that the trained artificial neural network (ANN) can improve the estimation error and correlation of the variables for both calibration and validation periods even when there is a low temporal consistency between the time series of th...

Understanding Flood Seasonality and Its Temporal Shifts within the Contiguous United States

Abstract: Understanding the causes of flood seasonality is critical for better flood management. This study examines the seasonality of annual maximum floods (AMF) and its changes before and after 1980 at over 250 natural catchments across the contiguous United States. Using circular statistics to define a seasonality index, the analysis focuses on the variability of the flood occurrence date. Generally, catchments with more synchronized seasonal water and energy cycles largely inherit their seasonality of AMF from that of annual maximum rainfall (AMR). In contrast, the seasonality of AMF in catchments with loosely synchronized water and energy cycles are more influenced by high antecedent storage, which is responsible for the amplification of the seasonality of AMF over that of AMR. This understanding then effectively explains a statistically significant shift of flood seasonality detected in some catchments in the recent decades. Catchments where the antecedent soil water storage has increased since 1980 ...

Bias Correction of Long-Term Satellite Monthly Precipitation Product (TRMM 3B43) over the Conterminous United States

Abstract: The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) has provided a valuable precipitation dataset for hydrometeorological studies (1998–2015). However, TMPA shows some differences when compared to the ground-based estimates. In this study, a correction model is developed to improve the accuracy of the TRMM precipitation monthly product by reducing the bias compared to the ground-based estimates. The TRMM 3B43 precipitation product is compared with the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) and with gridded precipitation estimates acquired from the CPC Unified Precipitation Project, two ground-based precipitation estimates, in the conterminous United States. The bias between the satellite and ground-based estimates is compared with mean surface temperature and elevation, respectively. A weak linear relationship is observed between the bias and temperature but a moderate inverse linear relationship is observed between the bias and ...