TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States

Research output: Contribution to conferencePoster

Standard

TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States. / Hossein Hashemi, Matias Nordin, Venkat Lakshmi, and Rosemary Knight.

2016.

Research output: Contribution to conferencePoster

Harvard

Hossein Hashemi, Matias Nordin, Venkat Lakshmi, and Rosemary Knight 2016, 'TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States'.

APA

Hossein Hashemi, Matias Nordin, Venkat Lakshmi, and Rosemary Knight (2016). TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States.

CBE

Hossein Hashemi, Matias Nordin, Venkat Lakshmi, and Rosemary Knight. 2016. TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States.

MLA

Hossein Hashemi, Matias Nordin, Venkat Lakshmi, and Rosemary Knight TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States. 2016.

Vancouver

Hossein Hashemi, Matias Nordin, Venkat Lakshmi, and Rosemary Knight. TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States. 2016.

Author

Hossein Hashemi, Matias Nordin, Venkat Lakshmi, and Rosemary Knight. / TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States.

RIS

TY - CONF

T1 - TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States

AU - Hashemi, Hossein

AU - Hossein Hashemi, Matias Nordin, Venkat Lakshmi, and Rosemary Knight

PY - 2016/12/12

Y1 - 2016/12/12

N2 - Precipitation can be quantified using a rain gauge network, or a remotely sensed precipitation product. Ultimately, the choice of dataset depends on the particular application, the catchment size, climate and the time period of study. In a region with a long record and a dense rain gauge network, the elevation-modified ground-based precipitation product, PRISM, has been found to work well. However, in poorly gauged regions the use of remotely sensed precipitation products is an absolute necessity. The Tropical Rainfall Measuring Mission (TRMM) has provided valuable precipitation datasets for hydrometeorological studies over the past two decades (1998-2015). One concern regarding the usage of TRMM data is the accuracy of the precipitation estimates, when compared to those obtained using PRISM. The reason for this concern is that TRMM and PRISM do not always agree and, typically, TRMM underestimates PRISM over the mountainous regions of the United States.In this study, we develop a correction function to improve the accuracy of the TRMM monthly product (TRMM-3B43) by estimating and removing the bias in the satellite data using the ground-based precipitation product, PRISM. We observe a strong relationship between the bias and land surface elevation; TRMM-3B43 tends to underestimate the PRISM product at altitudes greater than 1500 m above mean sea level (m.amsl) in the contiguous United States. A relationship is developed between TRMM-PRISM bias and elevation. The correction function is used to adjust the TRMM monthly precipitation using PRISM and elevation data. The model is calibrated using 25% of the available time period and the remaining 75% of the time period is used for validation. The corrected TRMM-3B43 product is verified for the high elevations over the contiguous United States and two local regions in the mountainous areas of the western United States. The results show a significant improvement in the accuracy of the TRMM product in the high elevations of the contiguous United States.

AB - Precipitation can be quantified using a rain gauge network, or a remotely sensed precipitation product. Ultimately, the choice of dataset depends on the particular application, the catchment size, climate and the time period of study. In a region with a long record and a dense rain gauge network, the elevation-modified ground-based precipitation product, PRISM, has been found to work well. However, in poorly gauged regions the use of remotely sensed precipitation products is an absolute necessity. The Tropical Rainfall Measuring Mission (TRMM) has provided valuable precipitation datasets for hydrometeorological studies over the past two decades (1998-2015). One concern regarding the usage of TRMM data is the accuracy of the precipitation estimates, when compared to those obtained using PRISM. The reason for this concern is that TRMM and PRISM do not always agree and, typically, TRMM underestimates PRISM over the mountainous regions of the United States.In this study, we develop a correction function to improve the accuracy of the TRMM monthly product (TRMM-3B43) by estimating and removing the bias in the satellite data using the ground-based precipitation product, PRISM. We observe a strong relationship between the bias and land surface elevation; TRMM-3B43 tends to underestimate the PRISM product at altitudes greater than 1500 m above mean sea level (m.amsl) in the contiguous United States. A relationship is developed between TRMM-PRISM bias and elevation. The correction function is used to adjust the TRMM monthly precipitation using PRISM and elevation data. The model is calibrated using 25% of the available time period and the remaining 75% of the time period is used for validation. The corrected TRMM-3B43 product is verified for the high elevations over the contiguous United States and two local regions in the mountainous areas of the western United States. The results show a significant improvement in the accuracy of the TRMM product in the high elevations of the contiguous United States.

M3 - Poster

ER -