nasa-gesdisc/es-publications-researchareas huggingface dataset:
Recent catastrophic landslide lake outburst floods in the Himalayan mountain range (2017)

Among the more complex and devastating interactions between climate and hydromorphological processes in mountain environments are landslide lake outburst floods (LLOFs), resulting from mass movements temporarily blocking a drainage system. This work reviews these processes in the Himalayas and highlights the high frequency of this type of phenomenon in the region. In addition, we analyse two recent catastrophic trans-national LLOFs occurring in the Sutlej river basin during 2000 and 2005. Based on high resolution satellite images, Tropical Rainfall Measuring Mission (TRMM), Moderate-Resolution Imaging Spectroradiometer (MODIS) derived evolution of snowline elevation and discharge data we reconstruct the timing and hydrometeorological conditions related to the formation and failure of landslide dams. Results showed that the 2005 flood, originating from the outburst of the Parchu Lake, was not related to heavy precipitation, but was likely enhanced by the rapid and late snowmelt of an unusually deep and widespread snowpack. The flood in 2000 was triggered by the outburst of an unnamed lake located on the Tibetan plateau, identified here for the first time. In this case, the outburst followed intense precipitation in the lake watershed, which raised the level of the lake and thus caused the breaching of the dam. As stream gauges were damaged during the events detailed discharge data is not available, but we estimated the peak discharges ranging between 1100 m3 s1 and 2000 m3 s1 in 2005, and 1024 m3 s1 and 1800 m3 s1 in 2000. These events caused significant geomorphic changes along the river valleys, with observed changes in channel width exceeding 200 m. Results also demonstrate that remotely-sensed data enables valuable large-scale monitoring of lake development and related hydrometeorological conditions, and may thereby inform early warning strategies, and provide a basis for flood risk reduction measures that focus on disaster preparedness and response strategies.

Research areas: Land Surface/Agriculture Indicators, Floods, Cryospheric Indicators
Role of inertial instability in the West African monsoon jump (2015)

AbstractThe West African monsoon jump is a sudden shift in the latitude of the West African precipitation maximum from the Guinean coast near 4N into Sahel near 12N in late June or early July. An examination of reanalyses and observations indicates that the Sahel rainy season develops smoothly and the monsoon jump occurs because of an abrupt decrease in Guinean coast rainfall. We show that this abrupt end of the coastal rainy season occurs when inertial instability develops over the region, 1 month later than it develops in the vicinity of the marine Atlantic Intertropical Convergence Zone. The reason for this delay is the presence of the African easterly jet, which places strong negative meridional zonal wind gradients over the coast to preserve the inertially stable environment. When the African easterly jet moves farther north due to the seasonal solar forcing, these gradients weaken and then reverse to satisfy the threshold condition for inertial instability; the rapid end of the Guinean coast rainy season follows. The northward movement and intensity of the African easterly jet are controlled by the seasonal development of strong meridional land surface temperature gradients and are independent of the formation of the Atlantic cold tongue. This explanation for the West African monsoon jump relates the phenomenon to the shape and location of the African continent, including the low-latitude position of the Guinean coast and the large expanse of the continent to the north.

Research areas: Atmospheric/Ocean Indicators
Age, extent and carbon storage of the central Congo Basin peatland complex (2017)

Peatlands are carbon-rich ecosystems that cover just three per cent of Earths land surface1, but store one-third of soil carbon2. Peat soils are formed by the build-up of partially decomposed organic matter under waterlogged anoxic conditions. Most peat is found in cool climatic regions where unimpeded decomposition is slower, but deposits are also found under some tropical swamp forests2,3. Here we present field measurements from one of the worlds most extensive regions of swamp forest, the Cuvette Centrale depression in the central Congo Basin4. We find extensive peat deposits beneath the swamp forest vegetation (peat defined as material with an organic matter content of at least 65 per cent to a depth of at least 0.3 metres). Radiocarbon dates indicate that peat began accumulating from about 10,600 years ago, coincident with the onset of more humid conditions in central Africa at the beginning of the Holocene5. The peatlands occupy large interfluvial basins, and seem to be largely rain-fed and ombrotrophic-like (of low nutrient status) systems. Although the peat layer is relatively shallow (with a maximum depth of 5.9 metres and a median depth of 2.0 metres), by combining in situ and remotely sensed data, we estimate the area of peat to be approximately 145,500 square kilometres (95 per cent confidence interval of 131,900156,400 square kilometres), making the Cuvette Centrale the most extensive peatland complex in the tropics. This area is more than five times the maximum possible area reported for the Congo Basin in a recent synthesis of pantropical peat extent2. We estimate that the peatlands store approximately 30.6 petagrams (30.6  1015 grams) of carbon belowground (95 per cent confidence interval of 6.346.8 petagrams of carbon)a quantity that is similar to the above-ground carbon stocks of the tropical forests of the entire Congo Basin6. Our result for the Cuvette Centrale increases the best estimate of global tropical peatland carbon stocks by 36 per cent, to 104.7 petagrams of carbon (minimum estimate of 69.6 petagrams of carbon; maximum estimate of 129.8 petagrams of carbon2). This stored carbon is vulnerable to land-use change and any future reduction in precipitation7,8.

Research areas: Ecosystems
Neotectonically triggered instability around the palaeolake regime in Central Kumaun Himalaya, India (2015)

Mass wasting often results from the combined effect of tectonic and climate processes. It has not only resulted in human casualties on large scale but has also ruined agricultural land and disrupted hydro power projects and other governmental as well as private property. Despite the belief that prevention is inevitably better than cure, decrease in future hazards requires proper dissemination of knowledge to the Himalayan inhabitants. Considering this, we investigated a part of Kumaun Himalaya to understand the cause of cloud burst induced mass movements along the Saryu River that took place on 18th August 2010 and subsequently on 1214th September, 2012. A number of Quaternary faults, e.g., Dulam fault (DF), Dulam Gadhera Fault (DGF) and Vongarh-Gason Fault (VGF) in the zone of a major thrust (Berinag Thrust) in the studied sector are invariably active as evident by various geomorphic features, e.g., saw cutting of host rocks, immature topography, deflecting river courses, ponding of ancient drainage, development of cascades, formation of unpaired fluvial terraces, and series of triangular fault facets. The fragile lithology, deep V shaped valleys, accelerating erosion and incision with higher uplift due to tectonic upheaval along the active faults are also responsible for rainfall induced catastrophes in the region. Additionally, morphometric analysis reveals that the Saryu basin is elongated and tilted. Further, the tectonic tilting and moderate to coarse drainage density may possibly be responsible for quicker runoff, amplified erosion, and subsequently increased flooding around the study area. We infer that the area is not only controlled by topography but may also have been affected by the hydraulic factors such as climate. In addition, the drainage is dominated mostly by first order streams which seem to be indicative of higher chances of flooding, as most of the water is concentrated in a single channel during monsoon season. We believe that the similar studies done in the other sectors will be helpful in reducing not only the huge loss of life but may also help in protecting ongoing and huge hydropower and other developmental projects in this newly born state.

Research areas: Land Surface/Agriculture Indicators
Long-term study of aerosolcloudprecipitation interaction over the eastern part of India using satellite observations during pre-monsoon season (2019)

This study attempts to analyze possible aerosolcloudprecipitation interaction over the eastern part of India including Bhubaneswar city and the whole Odisha region primarily using a long-term satellite-based dataset from 2000 to 2016 during pre-monsoon period. Relationship between aerosol optical depth (AOD), rainfall, and cloud properties is examined by taking convectively driven rain events. The two-sample students t test is used to compute p value of datasets that are statically significant. Role of aerosols in governing cloud properties is analyzed through the variation of COD (cloud optical depth) and CER (cloud effective radius) in the AOD ranges 0.20.8. A relatively stronger and affirmative AODCER relationship is observed over Bhubaneswar city compared to Odisha region though the aerosols still play an appreciable role for the later too. The AODCOD relationship is weak over both the regions. For Odisha, relationships between aerosol and cloud parameters are insignificant irrespective of rainfall regimes. Fostering of heavy rainfall over these regions takes place due to invigoration and microphysical effect during pre-monsoon months, depending upon meteorological conditions. Liquid water content and presence of a mixed-phase zone, both seem to be quite important in the convectively driven precipitation over Odisha region including Bhubaneswar city.

Research areas: Atmospheric/Ocean Indicators
Lake outburst and debris flow disaster at Kedarnath, June 2013: hydrometeorological triggering and topographic predisposition (2016)

Heavy rainfall in June 2013 triggered flash flooding and landslides throughout the Indian Himalayan state of Uttarakhand, killing more than 6000 people. The vast majority of fatalities and destruction resulted directly from a lake outburst and debris flow disaster originating from above the village of Kedarnath on June 16 and 17. Here, we provide a systematic analysis of the contributing factors leading to the Kedarnath disaster, both in terms of hydrometeorological triggering and topographic predisposition. Topographic characteristics of the lake watershed above Kedarnath are compared with other glacial lakes across the north-western Himalayan states of Uttarakhand and Himachal Pradesh, and implications for glacier lake outburst hazard assessment in a changing climate are discussed. Our analysis suggests that the early onset of heavy monsoon rainfall (390 mm, June 1017) immediately following a 4-week period of unusually rapid snow cover depletion and elevated streamflow was the crucial hydrometeorological factor, resulting in slope saturation and significant run-off into the small seasonal glacial lake. Between mid-May and mid-June 2013, snow-covered area above Kedarnath decreased by around 50 %. The unusual situation of the lake being dammed in a steep, unstable paraglacial environment but fed entirely from snowmelt and rainfall within a fluvial dominated watershed is important in the context of this disaster. A simple scheme enabling large-scale recognition of such an unfavourable topographic setting is introduced. In view of projected 21st century changes in monsoon timing and heavy precipitation in South Asia, more emphasis should be given to potential hydrometeorological triggering of lake outburst and debris flow disasters in the Himalaya.

Research areas: Floods, Land Surface/Agriculture Indicators, Atmospheric/Ocean Indicators, Cryospheric Indicators
Improved understanding of an extreme rainfall event at the Himalayan foothills  a case study using COSMO (2015)

In recent years, an increased occurrence of loss and damage of property and human casualties over the southern rim area of the Himalayas, caused by landslides following intense rainfall events, has been reported. An analysis of Tropical Rainfall Measuring Mission (TRMM)-gridded rainfall data shows that events with an exceedance probability of 1.6% for 200 mm/d rainfall are common over this region during the monsoon season. An improved understanding of the mechanisms, which lead to such events, is important for their prediction and to estimate the impact of climate change on their recurrence. In this study, we analyse such an extreme precipitation event, which hit the Uttarakhand region of the central Himalayas on 13 September 2012. We use the operational regional weather forecast model COSMO at a convection-permitting resolution of 2.8 km to simulate this event. The spatial pattern of daily-accumulated precipitation and atmospheric state profiles simulated by the model compared well with the TRMM-gridded data and radiosonde observations, which adds confidence to our model results. Our analysis suggests a three-step mechanism leading to this event: (1) development of an easterly low-level wind along the Gangetic Plain caused by a low pressure system over the central Gangetic Plain; (2) convergence of moisture over the north-western part of India, leading to an increase of potential instability of the air mass along the valley recesses, which is capped by an inversion located above the ridgeline; and (3) strengthening of the north-westerly flow above the ridges, which supports the lifting of the potentially unstable air over the protruding ridge of the foothills of the Himalayas and triggers shallow convection, which on passing through adjacent folds initiates deep convection.

Research areas: Atmospheric/Ocean Indicators
Importance of satellite-retrieved rain/no-rain information on short-range weather predictions (2017)

The impact of assimilating rain (satellite-retrieved rainfall is greater than zero) and no-rain (satellite-retrieved rainfall is equal to zero) information retrieved from the Tropical Rainfall Measuring Mission (TRMM) 3B42 precipitation is assessed during Indian summer monsoon 2013 using the weather research and forecasting (WRF) model. Daily three parallel experiments are performed with and without satellite rainfall assimilation for short-range weather forecasts. Additional two experiments are performed daily to evaluate the sensitivity of cumulus parameterization on the WRF model predictions when precipitations are used for assimilation. Precipitation assimilation improves the 48 h low-level temperature, moisture, and winds predictions. Rainfall prediction is also improved over central India when satellite-retrieved rainfall information are assimilated compared to without rainfall assimilation (CNT) experiments. More improvements are seen in moisture forecasts when the KainFritsch (KF) cumulus convection parameterization scheme is used against the GrellDevenyi ensemble (GD) scheme, whereas for temperature and wind speed forecasts the Grell convection parameterization scheme performed better over the Indian region. Overall, precipitation assimilation improved the WRF model analysis and subsequent model forecasts compared with without precipitation assimilation experiments. Results show that no-rain observations also have a significant positive impact on short-range weather forecasts.

Research areas: Validation
Impacts of woody plant encroachment on regional climate in the southern Great Plains of the United States (2013)

AbstractVegetation change can influence climate by altering the fluxes of mass and energy between ecosystems and the atmosphere. In the past century or so, rapid conversion of grasslands to woodland by woody species encroachment is one of the most important vegetation changes in the semiarid and arid regions of the world. The objective of this study is to investigate potential impacts of this widespread phenomenon on climate system in the southern Great Plains of the United States. The Regional Atmospheric Modeling System (RAMS) is used for this study. Grassland on the surface in RAMS is gradually replaced by woody species and RAMS is run a set of times, each with a different amount of encroachment. RAMS-simulated precipitation and air temperature are then analyzed. This study finds tha t over a 1 year period woody plant encroachment leads to increase in rainfall and the increase is statistically significant at many locations. Woody encroachment also has an overall warming effect, but increase in temperature is not statistically significant. Temperature and precipitation increase almost linearly with increasing encroachment on the surface. When grassland is completely replaced, annual accumulated precipitation increases by 23.6 mm and maximum air temperature rises by 0.13C averaged over the entire study area. In areas where encroachment occurs, averaged increases in accumulated precipitation and temperature are 58.2 mm and 0.27C, respectively. The largest increase in precipitation and strongest warming tend to be located in dry and encroached areas including central and northern Texas, and they reach as high as 213.6 mm and 0.68C, respectively. Decrease in surface albedo is found to be the most important factor that causes these changes.

Research areas: Land Surface/Agriculture Indicators, Atmospheric/Ocean Indicators
Impact of additional surface observation network on short range weather forecast during summer monsoon 2008 over Indian subcontinent (2011)

The three dimensional variational data assimilation scheme (3D-Var) is employed in the recently developed Weather Research and Forecasting (WRF) model. Assimilation experiments have been conducted to assess the impact of Indian Space Research Organisations (ISRO) Automatic Weather Stations (AWS) surface observations (temperature and moisture) on the short range forecast over the Indian region. In this study, two experiments, CNT (without AWS observations) and EXP (with AWS observations) were made for 24-h forecast starting daily at 0000 UTC during July 2008. The impact of assimilation of AWS surface observations were assessed in comparison to the CNT experiment. The spatial distribution of the improvement parameter for temperature, relative humidity and wind speed from one month assimilation experiments demonstrated that for 24-h forecast, AWS observations provide valuable information. Assimilation of AWS observed temperature and relative humidity improved the analysis as well as 24-h forecast. The rainfall prediction has been improved due to the assimilation of AWS data, with the largest improvement seen over the Western Ghat and eastern India.

Research areas: Validation
Extreme weather and economic well-being in rural Mozambique (2013)

Societies dependent on rain-fed agriculture are highly vulnerable to weather extremes; thus, linkages between rainfall variability and economic well-being merit close attention. The hypothesis of this paper is that rainfall patterns impact changes in income within our study region of central and northern Mozambique. Utilizing satellite-based estimates of rainfall analyzed within a GIS, we establish a 12-year rainfall climatology and calculate monthly rainfall anomalies for 419 villages during three growing seasons. We also approximate storm-total rainfall from tropical cyclones entering the Mozambique Channel. Hierarchical cluster analysis groups the villages according to the monthly rainfall anomalies and rainfall received from Cyclones Delfina and Japhet. Then, using data from the National Agricultural Survey of Mozambique conducted in 2002 and 2005, we relate rainfall and change in income through the calculation of Pearsons correlation coefficients and independent-samples t tests using village-groups produced by the cluster analysis. We find that no season closely approximates the 12-year climatology and that rainfall varied among the three seasons. Although most villages experience income declines, those affected by Delfina exhibit the worst economic performance, indicating that heavy rainfall from some tropical cyclones can have long-lasting negative effects on income. Additionally, receiving above-normal rainfall may hinder economic well-being more than below-normal rainfall. Our study identifies patterns in sub-national rainfall variability and economic well-being that enable a more detailed understanding of weather-related effects on socio-economic outcomes.

Research areas: Atmospheric/Ocean Indicators, Severe Storms, Agriculture
Climate-driven chlorophyll-a changes in a turbid estuary: Observations from satellites and implications for management (2013)

Significant advances have been made in ocean color remote sensing of turbidity and water clarity for estuarine waters, yet accurate estimations of chlorophyll-a concentrations (Chla in mgm3) has been problematic, posing a challenge to the research community and an obstacle to managers for long-term water quality assessment. Here, a novel empirical Chla algorithm based on a Red-Green-Chorophyll-Index (RGCI) was developed and validated for MODIS and SeaWiFS observations between 1998 and 2011. The algorithm showed robust performance with two independent datasets, with relative mean uncertainties of ~30% and ~50% and RMS uncertainties of ~40% and ~65%, respectively, for Chla ranging between 1.0 and >30.0mgm3. These uncertainties are comparable or even lower than those reported for the global open oceans when traditional blue-green band ratio algorithms are used. A long-term Chla time series generated from SeaWiFS and MODIS observations showed excellent agreement between sensors and with in situ measurements. Substantial variability in both space and time was observed in the four bay segments, with higher Chla in the upper bay segments and lower Chla in the lower bay segments, and higher Chla in the wet season and lower Chla in the dry season. On average, river discharge could explain ~60% of the seasonal changes and ~90% of the inter-annual changes, with the latter mainly driven by climate variability (e.g. El Nino and La Nina years) and anomaly events (e.g. tropical cyclones). Significant positive correlation was found between monthly mean Chla anomalies and monthly Multivariate ENSO Index (MEI) (Pearson correlation coefficient=0.43, p<0.01, N=147), with high Chla associated with El Nino and lower Chla associated with La Nina. Further, a Water Quality Decision Matrix (WQDM) was established from satellite observations, providing complementary and more reliable information to the existing WQDM based on less synoptic and less frequent field measurements. The satellite-derived WQDM and long-term time-series data support the decision making efforts of the management agencies that regulate nutrient discharge to the bay. Similar approaches may be established for other estuaries where field data are much more limited than for Tampa Bay.

Research areas: Ecosystems, Atmospheric/Ocean Indicators
Changes in local oceanographic and atmospheric conditions shortly after the 2004 Indian Ocean tsunami (2015)

This study examines changes in the local oceanographic and atmospheric conditions over the southern Bay of Bengal and adjacent Indian Ocean waters after the 2004 Indian Ocean tsunami based on satellite remote sensing data and atmospheric reanalysis fields. After the tsunami that occurred on 26 December 2004, the accumulated rainfall had a notably increase (600 mm per month) in January of 2005 over deep waters to the southeast of Sri Lanka. This rainfall increase after the tsunami was accompanied with cooling in the sea surface temperature (SST) (up to 2 C). Four-day averaged SST anomalies had a noticeable increase (14 C) after the tsunami over the deep waters to the southwest of the epicenter. Series of ocean atmospheric and biological variables changed successively after the change of SST. The chain of causality between the tsunami and the changes in the local atmospheric conditions is suggested.

Research areas: Earthquakes