nasa-gesdisc/es-publications-researchareas huggingface dataset:
Assessment of the TRMM 3B42 Precipitation Product in Southern Brazil (2016)

The increase in the use of satellite-derived precipitation products generated by different methods and algorithms emphasizes the need for a deeper analysis of their quality and accuracy. Using the contingency table method, we evaluated the accuracy of versions 6 and 7 of the Tropical Rainfall Measuring Mission Precipitation (TRMM) 3B42 product in southern Brazil by comparing daily precipitation over 13 years (V6 was tested for historical context). The interpolated data from 25 rain gauges were compared with both versions of TRMM. The V7 product tended to produce a slight increase in PC (proportion correct). V7 also showed a slight increase in the correlation coefficient (CC) and a significant increase in the H (hit rate) and CSI (critical success) indexes. However, the upgraded version shows an undesirable increase in the false alarm ratio. When the rainfall volumes were compared, V6 clearly underestimated the total rainfall over the entire period, but the V7 product slightly overestimated the cumulative volume (11%) which still represented a more reliable estimate than from V6. Furthermore, the main improvement in V7 was a large increase in the quantitative recognition of extreme precipitation events: V6 detected only 1% of the daily rainfalls above 60 mm, whereas V7 detected 57% of the events.

Research areas: Validation
Geomorphology and the controls of geohydrology on waterlogging in Gangetic Plains, North Bihar, India (2014)

Waterlogging is a complex phenomenon, the severity of which depends on a number of natural as well as anthropogenic factors. The present study pertains to the evaluation of control exerted by various factors, viz geomorphology, relief, groundwater fluctuation, rainfall, catchment area and canalroad network density, on waterlogging in the north Bihar region of Gangetic Plains. Satellite images IRS P6 LISS III acquired in the years 2005 and 2006 were used to map temporal variability in surface waterlogging which revealed a reduction of 52 % in the waterlogging area during the pre-monsoon. The seasonal groundwater fluctuation was examined using 20052006 pre- and post-monsoon water level data. It clearly indicated that a large portion of the area was also under highly critical groundwater level occurring at a depth of less than 1 m belowground surface during the post-monsoon periods. The percentage of waterlogged area per square kilometer in each geomorphological unit clearly depicts that the Kosi megafan (Lower), because of a high density of paleochannels, comprises the highest post-monsoon waterlogged area. The Tropical Rainfall Measuring Mission (TRMM) data were analyzed for the period 19982009 to examine the spatial variability of rainfall over the entire catchment during the monsoon period. The high incidence of post-monsoon surface waterlogging delineated through satellite data and high average rainfall (>1,100 mm) in the same area indicates a positive relationship between rainfall and surface waterlogging. Waterlogging is more prominent in the lower relief zones, but anomalous relative rise in waterlogging within 4050 m of relief zone was attributed to anthropogenic factors primarily related to the development of canal network.

Research areas: Land Surface/Agriculture Indicators
A short note on linkage of climatic records between a river valley and the upper timberline in the Sygera Mountains, southeastern Tibetan Plateau (2011)

Tree-ring data from timberlines have been widely used to reconstruct past temperature variability. High-quality reconstructions depend on successful calibrations in which tree-ring records are compared with instrumental observations of climatic factors to establish quantitative relationships between tree growth and climate. Climatic data used in the calibrations are mostly from nearby meteorological stations, located generally in the valleys near human settlements of mountainous areas, regardless of whether climatic records at low elevations are representative for the upper timberline. In order to better understand the characteristics of the alpine environment at the upper timberline of blackseed juniper (Juniperus saltuaria) in the eastern side of the Sygera Mountains, southeastern Tibetan Plateau, an automatic weather station was established. We found that the variation in the daily/5-day/10-day/monthly mean temperatures and sums of precipitation on the valley bottom (3000ma.s.l.) as well as the daily/seasonal sums of precipitation from the TRMM (Tropical Rainfall Measuring Mission) are highly correlated with the measurements at the upper timberline (4400ma.s.l.). Thus, the variations of the valley bottom temperature and precipitation records are confident indicators of the conditions at the upper timberline on the southeastern Tibetan Plateau and hence can be used for the calibration in the dendroclimatic reconstructions based on timberline tree-ring data. For 5-day mean temperature pooled by individual months, the R2 values of the regression models>0.60 between the valley bottom and timberline in FebruaryAugust and October, and <0.40 in December. For 5-day total precipitation, the R2 values>0.60 in MarchJuly and OctoberDecember, and <0.40 in January, February, August and September. This study represents a small step towards fixing problems regarding to dendroclimatic calibrations.

Research areas: Atmospheric/Ocean Indicators
Evaluation of five satellite products for estimation of rainfall over Uganda / Evaluation de cinq produits satellitaires pour l'estimation des precipitations en Ouganda (2008)

Five satellite-based rainfall estimation algorithms (TRMM 3B42, CMORPH, TAMSAT, RFE 2.0 and PERSIANN) are assessed against historical monthly rainfall statistics from raingauges within four regions of Uganda. Results are discussed in terms of the accuracy of the products, the effect of climate variability, and differences between products. Products are able to reasonably reflect seasonal patterns in rainfall, and also the spatial patterns in rainfall between regions. Patterns in the occurrence of rainfall are better reflected than patterns in rainfall amounts. There is significant scope for improving the estimation of amounts by calibration to the raingauge data. TRMM 3B42, CMORPH and TAMSAT show most promise in this application followed by RFE 2.0 and the PERSIANN system. However, the relative performance of the products depends on what aspects of the rainfall regime are being considered. Differences between the products are large and the use of more than one product for any application is recommended.

Research areas: Validation
Evaluation of satellite and simulated rainfall products for hydrological applications in the Notwane catchment, Botswana (2017)

In semi-arid catchments, hydrological modeling, water resources planning and management are hampered by insufficient spatial rainfall data which is usually derived from limited rain gauge networks. Satellite products are potential candidates to augment the limited spatial rainfall data in these areas. In this paper, the utility of the Tropical Rainfall Measuring Mission (TRMM) product (3B42 v7) is evaluated using data from the Notwane catchment in Botswana. In addition, rainfall simulations obtained from a multi-site stochastic rainfall model based on the generalised linear models (GLMs) were used as additional spatial rainfall estimates. These rainfall products were compared to the observed rainfall data obtained from six (6) rainfall stations available in the catchment for the period 19982012. The results show that in general the two approaches produce reasonable spatial rainfall estimates. However, the TRMM products provided better spatial rainfall estimates compared to the GLM rainfall outputs on an average, as more than 90% of the monthly rainfall variations were explained by the TRMM compared to 80% from the GLMs. However, there is still uncertainty associated mainly with limited rainfall stations, and the inability of the two products to capture unusually high rainfall values in the data sets. Despite this observation, rainfall indices computed to further assess the daily rainfall products (i.e. rainfall occurrence and amounts, length of dry spells) were adequately represented by the TRMM data compared to the GLMs. Performance from the GLMs is expected to improve with addition of further rainfall predictors. A combination of these rainfall products allows for reasonable spatial rainfall estimates and temporal (short term future) rainfall simulations from the TRMM and GLMs, respectively. The results have significant implications on water resources planning and management in the catchment which has, for the past three years, been experiencing prolonged droughts as shown by the drying of Gaborone dam (currently at a record low of 1.6% full), which is the main source of water supply to the city of Gaborone and neighbouring townships in Botswana.

Research areas: Validation
Characteristics of different convective parameterization schemes on the simulation of intensity and track of severe extratropical cyclones over North Atlantic (2018)

The role of the convective parameterization schemes (CPSs) in the ARW-WRF (WRF) mesoscale model is ex-
amined for extratropical cyclones (ETCs) over the North Atlantic Ocean. The simulation of very severe winter
storms such as Xynthia (2010) and Gong (2013) are considered in this study. Most popular CPSs within WRF
model, along with Yonsei University (YSU) planetary boundary layer (PBL) and WSM6 microphysical para-
meterization schemes are incorporated for the model experiments. For each storm, four numerical experiments
were carried out using New Kain Fritsch (NKF), Betts-Miller-Janjic (BMJ), Grell 3D Ensemble (Gr3D) and no
convection scheme (NCS) respectively. The prime objectives of these experiments were to recognize the best CPS
that can forecast the intensity, track, and landfall over the Iberian Peninsula in advance of two days. The WRF
model results such as central sea level pressure (CSLP), wind field, moisture flux convergence, geopotential
height, jet stream, track and precipitation have shown sensitivity CPSs. The 48-hour lead simulations with BMJ
schemes produce the best simulations both regarding ETCs intensity and track than Gr3D and NKF schemes. The
average MAE and RMSE of intensities are least that (6.5 hPa in CSLP and 3.4 ms  1 in the 10-m wind) found in
BMJ scheme. The MAE and RMSE for and intensity and track error have revealed that NCS produces large errors
than other CPSs experiments. However, for track simulation of these ETCs, at 72-, 48- and 24-hour means track
errors were 440, 390 and 158 km respectively. In brevity, BMJ and Gr3D schemes can be used for short and
medium range predictions of the ETCs over North Atlantic. For the evaluation of precipitation distributions using
Gr3D scheme are good agreement with TRMM satellite than other CPSs.

Research areas: Severe Storms
Hydrologic Assessment of the Uncertainty of Six Remote Sensing Precipitation Estimates Driven by a Distributed Hydrologic Model in the Blue Nile Basin (2022)

Because of the sparseness of the ground monitoring network, precipitation estimations based on satellite products (PESPs) are currently requisite tools for hydrological simulation research and applications. The evaluation of six global high-resolution PESPs (TRMM 3B42V7, GPGP-1DD, TRMM 3B42RT, CMORPH-V1.0, PERSIANN, and PERSIANN-CDR) is the ultimate purpose of this research. Additionally, the distributed Hydrological River Basin Environmental Assessment Model (Hydro-BEAM) is used to investigate their potential effects in streamflow predictions over the Blue Nile basin (BNB) during the period 2001 to 2007. The correctness of the studied PESPs is assessed by applying categorical criteria to appraise their performances in estimating and reproducing precipitation amounts, while statistical indicators are utilized to determine their rain detection capabilities. Our findings reveal that TRMM 3B42V7 outperforms the remaining product in both the estimation of precipitation and the hydrological simulation, as reflected in highest NSE and R2 values ranges from 0.85 to 0.94. Generally, the TRMM 3B42V7 precipitation product exhibits tremendous potential as a substitute for precipitation estimates in the BNB, which will provide powerful forcing input data for distributed hydrological models. Overall, this study will hopefully provide a better comprehension of the usefulness and uncertainties of various PESPs in streamflow simulations, particularly in this region.

Research areas: Validation
Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series (2018)

The development, implementation and enforcement of policies involving the rational use of the land and the conservation of natural resources depend on an adequate characterization and understanding of the land cover, including its dynamics. This paper presents an approach for monitoring vegetation dynamics using high-quality time series of MODIS surface reflectance data by generating fraction images using Linear Spectral Mixing Model (LSMM) over South America continent. The approach uses physically-based fraction images, which highlight target information and reduce data dimensionality. Further dimensionality was also reduced by using the vegetation fraction images as input to a Principal Component Analysis (PCA). The RGB composite of the first three PCA components, accounting for 92.9% of the dataset variability, showed good agreement with the main ecological regions of South America continent. The analysis of 21 temporal profiles of vegetation fraction values and precipitation data over South America showed the ability of vegetation fractions to represent phenological cycles over a variety of environments. Comparisons between vegetation fractions and precipitation data indicated the close relationship between water availability and leaf mass/chlorophyll content for several vegetation types. In addition, phenological changes and disturbance resulting from anthropogenic pressure were identified, particularly those associated with agricultural practices and forest removal. Therefore the proposed method supports the management of natural and non-natural ecosystems, and can contribute to the understanding of key conservation issues in South America, including deforestation, disturbance and fire occurrence and management.

Research areas: Land Surface/Agriculture Indicators, Habitat Conversion/Fragmentation
Temporal Variations and Associated Remotely Sensed Environmental Variables of Dengue Fever in Chitwan District, Nepal (2018)

Dengue fever is one of the leading public health problems of tropical and subtropical countries across the world. Transmission dynamics of dengue fever is largely affected by meteorological and environmental factors, and its temporal pattern generally peaks in hot-wet periods of the year. Despite this continuously growing problem, the temporal dynamics of dengue fever and associated potential environmental risk factors are not documented in Nepal. The aim of this study was to fill this research gap by utilizing epidemiological and earth observation data in Chitwan district, one of the frequent dengue outbreak areas of Nepal. We used laboratory confirmed monthly dengue cases as a dependent variable and a set of remotely sensed meteorological and environmental variables as explanatory factors to describe their temporal relationship. Descriptive statistics, cross correlation analysis, and the Poisson generalized additive model were used for this purpose. Results revealed that dengue fever is significantly associated with satellite estimated precipitation, normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) synchronously and with different lag periods. However, the associations were weak and insignificant with immediate daytime land surface temperature (dLST) and nighttime land surface temperature (nLST), but were significant after 45 months. Conclusively, the selected Poisson generalized additive model based on the precipitation, dLST, and NDVI explained the largest variation in monthly distribution of dengue fever with minimum Akaikes Information Criterion (AIC) and maximum R-squared. The best fit model further significantly improved after including delayed effects in the model. The predicted cases were reasonably accurate based on the comparison of 10-fold cross validation and observed cases. The lagged association found in this study could be useful for the development of remote sensing-based early warning forecasts of dengue fever.

Research areas: Public Health
An assessment of mean areal precipitation methods on simulated stream flow: a SWAT model performance assessment (2017)

Accurate mean areal precipitation (MAP) estimates are essential input forcings for
hydrologic models. However, the selection of the most accurate method to estimate MAP can
be daunting because there are numerous methods to choose from (e.g., proximate gauge, direct
weighted average, surface-fitting, and remotely sensed methods). Multiple methods (n = 19) were
used to estimate MAP with precipitation data from 11 distributed monitoring sites, and 4 remotely
sensed data sets. Each method was validated against the hydrologic model simulated stream flow
using the Soil and Water Assessment Tool (SWAT). SWAT was validated using a split-site method and
the observed stream flow data from five nested-scale gauging sites in a mixed-land-use watershed
of the central USA. Cross-validation results showed the error associated with surface-fitting and
remotely sensed methods ranging from  4.5% to  5.1%, and  9.8% to  14.7%, respectively. Split-site
validation results showed the percent bias (PBIAS) values that ranged from  4.5% to  160%. Second
order polynomial functions especially overestimated precipitation and subsequent stream flow
simulations (PBIAS =  160) in the headwaters. The results indicated that using an inverse-distance
weighted, linear polynomial interpolation or multiquadric function method to estimate MAP may
improve SWAT model simulations. Collectively, the results highlight the importance of spatially
distributed observed hydroclimate data for precipitation and subsequent steam flow estimations.
The MAP methods demonstrated in the current work can be used to reduce hydrologic model
uncertainty caused by watershed physiographic differences.

Research areas: Validation
A study on the role of land-atmosphere coupling on the south Asian monsoon climate variability using a regional climate model (2017)

Land-atmosphere coupling over the south Asian monsoon region is examined using a regional climate model. For this purpose, the Weather Research and Forecasting (WRF) model with a resolution of 45 km was used. In the control experiment (CTL), the model was integrated from the year 2000 to 2011 and allowed the soil moisture interaction with the atmosphere using a coupled land surface model. In the second experiment (CSM), the soil moisture evolution at each time step was replaced with the climatology of soil moisture taken from the control run. The results reveal that land-atmosphere coupling plays a critical role in influencing the south Asian monsoon climate variability. Soil moisture is found to have stronger impacts on daily maximum temperature compared to minimum temperature. Soil moisture also makes a significant contribution to monsoon rainfall variability over the monsoon region. The coupling strength for large-scale rainfall is found to be higher compared to that of cumulus rainfall. Soil moisture is found more strongly coupled to sensible heat flux over most of the monsoon region.

Research areas: Validation
Impact of single-point GPS integrated water vapor estimates on short-range WRF model forecasts over southern India (2017)

Specifying physically consistent and accurate initial conditions is one of the major challenges of numerical weather prediction (NWP) models. In this study, ground-based global positioning system (GPS) integrated water vapor (IWV) measurements available from the International Global Navigation Satellite Systems (GNSS) Service (IGS) station in Bangalore, India, are used to assess the impact of GPS data on NWP model forecasts over southern India. Two experiments are performed with and without assimilation of GPS-retrieved IWV observations during the Indian winter monsoon period (NovemberDecember, 2012) using a four-dimensional variational (4D-Var) data assimilation method. Assimilation of GPS data improved the model IWV analysis as well as the subsequent forecasts. There is a positive impact of 10 % over Bangalore and nearby regions. The Weather Research and Forecasting (WRF) model-predicted 24-h surface temperature forecasts have also improved when compared with observations. Small but significant improvements were found in the rainfall forecasts compared to control experiments.

Research areas: Validation
Assessment of landslide hazards induced by extreme rainfall event in Jammu and Kashmir Himalaya, northwest India (2017)

In the Indian Himalayan region (IHR), landslide-driven hazards have intensified over the past several decades primarily caused by the occurrence of heavy and extreme rainfall. However, little attention has been given to determining the cause of events triggered during pre- and post-Indian Summer Monsoon (ISM) seasons. In the present research, detailed geological, meteorological, and remote sensing investigations have been carried out on an extreme rainfall landslide event that occurred in Sadal village, Udhampur district, Jammu and Kashmir Himalaya, during September 2014. Toward the receding phase of the ISM (i.e., in the month of September 2014), an unusual rainfall event of ~ 488.2 mm rainfall in 24 h took place in Jammu and Kashmir Himalaya in contrast to the normal rainfall occurrence. Geological investigations suggest that a planar weakness in the affected region is caused by bedding planes that consist of an alternate sequence of hard, compact sandstone and weak claystone. During this extreme rainfall event, the Sadal village was completely buried under the rock slides, as failure occurred along the planar weakness that dips toward the valley slope. Rainfall data analysis from the Tropical Rainfall Measuring Mission (TRMM) for the preceding years homogeneous time series (JulySeptember) indicates that the years 2005, 2009, 2011, 2012, and 2014 (i.e., closely spaced and clustering heavy rainfall events) received heavy rainfalls during the withdrawal of the ISM; whereas the heaviest rainfall was received in the years 2003 and 2013 at the onset of the ISM in the study region. This suggests that no characteristic cyclicity exists for extreme rainfall events. However, we observe that either toward the onset of the ISM or its retreat, the extreme rainfall facilitates landslides, rockfall, and slope failures in northwestern Himalaya. The spatiotemporal distribution of landslides caused by extreme rainfall events suggests its confinement toward the windward side of the Himalayan front.

Research areas: Land Surface/Agriculture Indicators, Atmospheric/Ocean Indicators