logo
calendar23 декабр 2024
view2
Asosiy til:Ingliz

IMPROVING THE ACCURACY OF CMIP5 TEMPERATURE DATA BY USING THE LINEAR SCALING BIAS CORRECTION METHOD

Fan yo'nalishi:
pdf

67690c7cdf3c5.pdf

PDF

MAQOLA ANNOTATSIYASI

quote
Annotatsiya. Iqlim o'zgarishining mintaqaviy miqyosdagi ta'sirini o'rganish uchun uzluksiz fazoviy meteorologik ma'lumotlar talab qilinadi. Ushbu maqolada 2000, 2010 va 2018-yillarda maksimal va minimal havo harorati ma'lumotlarini sozlash uchun oddiy chiziqli to'g'rilash usuli qo'llanilgan. Natijalar shuni ko'rsatadiki, agar balandlik effekti hisobga olinmasa, tog'li hududlarga qaraganda tekislikdagi joylarida to`g`irlash samarali natija beradi. Shunga qaramasdan, to`g`irlash oltita nuqtadan beshtasida muvaffaqiyatli amalga oshirildi.

MUALIFLAR

Teglar

# температура# accuracy# точность# aniqlik# harorat# temperature# CMIP5# linear scaling bias correction# Tashkent region.# chiziqli to`g`irlash# Toshkent viloyati# линейная коррекция смещения# Ташкентская область.

Maqolani baholang

0

0 ta

Maqola idintifikatorlari

Foydalanilgan adabiyotlar

1. Cao, W., Hu, J. X. and Yu, X. (2009) ‘A study on temperature interpolation methods based on GIS’, 2009 17th International Conference on Geoinformatics, Geoinformatics 2009. doi: 10.1109/ GEOINFORMATICS.2009.5293422

2. Erdanaev, E. et al. (2015) ‘Short Review of Climate and Land Use change Impact on Land Degradation in Tashkent Province.’, International Journal of Geoinformatics. doi: 10.52939/IJG.V11I4.909.

3. Gafforov, K. S. et al. (2020) ‘The assessment of climate change on rainfall-runoff erosivity in the Chirchik-Akhangaran Basin, Uzbekistan’, Sustainability (Switzerland), 12(8), p. 3369. doi: 10.3390/ SU12083369.

4. Graham, L. P., Andreáasson, J. and Carlsson, B. (2007) ‘Assessing climate change impacts on hydrology from an ensemble of regional climate models, model scales and linking methods – a case study on the Lule River basin’, Climatic Change 2007 81:1, 81(1), pp. 293–307. doi: 10.1007/S10584-006-9215-2.

5. Hawkins, E. et al. (2013) ‘Calibration and bias correction of climate projections for crop modelling: An idealised case study over Europe’, Agricultural and Forest Meteorology, 170, pp. 19–31. doi: 10.1016/J. AGRFORMET.2012.04.007.

6. Lenderink, G., Buishand, A. and Van Deursen, W. (2007) ‘Estimates of future discharges of the river Rhine using two scenario methodologies: direct versus delta approach’, Hydrology and Earth System Sciences, 11(3), pp. 1145–1159. doi: 10.5194/HESS-11-1145-2007.

7. Navarro-Racines, C. et al. (2020) ‘High-resolution and bias-corrected CMIP5 projections for climate change impact assessments’, Scientific Data 2020 7:1, 7(1), pp. 1–14. doi: 10.1038/s41597-019-0343

8. Shrestha, M., Acharya, S. C. and Shrestha, P. K. (2017) ‘Bias correction of climate models for hydrological modelling – are simple methods still useful?’, Meteorological Applications, 24(3), pp. 531–539. doi: 10.1002/MET.1655.

9. Soriano, E., Mediero, L. and Garijo, C. (2019) ‘Selection of bias correction methods to assess the impact of climate change on flood frequency curves’, Water (Switzerland), 11(11). doi: 10.3390/w11112266.

10. Teutschbein, C. and Seibert, J. (2012) ‘Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods’, Journal of Hydrology, 456–457, pp. 12–29. doi: 10.1016/J.JHYDROL.2012.05.052.

11. Viggiano, M. et al. (2019) ‘A new spatial modeling and interpolation approach for high-resolution temperature maps combining reanalysis data and ground measurements’, Agricultural and Forest Meteorology, 276–277, p. 107590. doi: 10.1016/J.AGRFORMET.2019.05.021.

public

SLIB.uz — O'zbekiston ilmiy jurnallari va maqolalar yagona tizimda ilmiy nashirlarni bir joyda ko'rish, izlash va ulardan foydalanish imkonini beruvchi zamonaviy platforma.

Ijtimoiy tarmoqlarda
instagramtelegramyoutubefacebook

Bog'lanish uchun

Manzil:Chilonzor tumani Qatortol ko'chasi 60B

Tel:+998(55)511-44-00

Savol-javob va takliflar uchun

© 2026 Barcha huquqlar himoyalangan.