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November 08, 2017, 10:37:36 PM by Karthikeyan L | Views: 162 | Comments: 0

A work carried out by Sonali Pattanayak titled "Linkage between global sea surface temperature and hydroclimatology of a major river basin of India before and after 1980" got published recently in the Environmental Research Letters.

Abstract: Frequent occurrence of flood and drought worldwide has drawn attention to assess whether the hydroclimatology of major river basins has changed. Mahanadi river basin (MRB) is the major source of fresh water for both Chattisgarh and Odisha states (71 million population approximately) of India. The MRB (141,600 km2 area) is one of the most vulnerable to climate change and variations in temperatures and precipitation regions. In the recent years, it has been repetitively facing the adverse hydrometeorological conditions. Large-scale ocean-atmospheric phenomena have substantial influence on river hydroclimatology. Hence Global sea surface temperature (SST) linkage with precipitation and surface temperature of MRB is analyzed over period 1950-2012. Significant changes in seasonal correlation patterns are witnessed from 1950-1980 (PR-80) to 1981-2012 (PO-80) periods. The correlation is higher during PR-80 compared to PO-80 between Niño region SST versus maximum temperature (Tmax) in all seasons except pre monsoon season and minimum temperature (Tmin) in all seasons except monsoon season. However, precipitation correlation changes are not prominent. Like SST, correlation patterns of sea level pressure with precipitation, Tmax and Tmin are shifted conspicuously from PR-80 to PO-80. These shifts could be related to change in Pacific decadal SST patterns and human induced anthropogenic effects. Fingerprint-based detection and attribution analysis revealed that the observed changes in Tmin (pre monsoon and monsoon season) during second half of the 20th century cannot be explained solely by natural variability and these changes can be attributed to human induced anthropogenic effect.

Sonali can be contacted at iisc.sonali@gmail.com
October 23, 2017, 12:13:28 PM by Karthikeyan L | Views: 244 | Comments: 2

Recently, I have published a couple of papers related to satellite microwave soil moisture research in the Advances in Water Resources Journal.

The process of retrieving soil moisture from satellite microwave sensors depends on the type of sensor i.e., active and passive microwave sensors. Over the past four decades, the microwave community has progressed in terms of improving the sensor design and retrieval algorithm so as to achieve accurate global scale soil moisture observations.

The first paper titled "Four decades of microwave satellite soil moisture observations: Part 1. A review of retrieval algorithms" gives a comprehensive overview of the developments that took place in the retrieval algorithms over the past four decades. The paper discusses the algorithmic developments of both active as well as passive sensors. We have also, for the first time, summarized the literature in the form of figures, one each for active and passive microwave soil moisture research (PFA). This review also discusses the latest developments in components of the algorithms, and also discusses the challenges that need attention in future. I can say that this paper serves as a starting point for someone who wants to venture into the field of microwave soil moisture research.

The second paper titled "Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons" is focused on assessing the accuracy of soil moisture products, which were developed over the past forty years. We have considered eight passive (SMMR, SSM/I, TMI, AMSR-E, WindSAT, AMSR2, SMOS, and SMAP), two active (ERS-Scatterometer, and MetOp-ASCAT), and one active-passive combined (ESA-CCI combined product) soil moisture products for the analysis. The Contiguous United States (CONUS) is considered as a case study. The validation is carried out using the data pertaining to 1058 stations over the CONUS, along with model soil moisture simulations obtained from the VIC land surface model. We analyzed these products in terms of daily coverage (a figure in this context is atteched with this post), temporal performance, and spatial performance. We also carried out inter-satellite comparisons to study the roles of sensor design and algorithms on the retrieval accuracy. The Part 1 serves as a prelude to this paper. Through these papers, one can get an idea about how well the satellites along with algorithms have progressed over the four decades and significantly improved the accuracy of soil moisture retrievals.

Part 1 can be downloaded for free from here: https://authors.elsevier.com/a/1VjkU16J1mlNrZ (until November 4, 2017)
Part 2 can be downloaded for free from here: https://authors.elsevier.com/a/1VoHy16J1mlNra (until November 17, 2017)

Here are the permanent links:
Part 1: http://www.sciencedirect.com/science/article/pii/S0309170817301859
Part 2: http://www.sciencedirect.com/science/article/pii/S0309170817301860

You can write an email to me at karthik120120@gmail.com for full-text requests or any other query related to papers.
October 23, 2017, 11:22:09 AM by Karthikeyan L | Views: 163 | Comments: 0

The work carried out by Ila Chawla along with Prof. P.P. Mujumdar titled "Partitioning Uncertainty in Streamflow Projections under Nonstationary Model Conditions" was recently published in the Advances in Water Resources Journal.

In this work, the authors, in a novel attempt, have addressed the possibility of nonstationary hydrological model (here they have used the VIC land surface model coupled with a routing model). They found that the hydrological model parameters, which are influenced by climate variables, vary over time, and thus may not be assumed to be stationary. Further, the work also involves attribution the total uncertainty in the streamflow projections to multiple effects such as, model parameters, GCM simulations, emission scenarios, land use scenarios, the assumption of hydrological model stationarity, along with internal variability of the model. The Upper Ganga Basin (UGB) is considered as a case study for this analysis.

Further details on the work can be found here: http://www.sciencedirect.com/science/article/pii/S0309170817300179

Authors are glad to share their article with interested readers.

Correspondence to: pradeep@iisc.ac.in
Pages: [1]

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