High-resolution Near-surface Soil Freeze/Thaw Status And Changes In Northern Hemisphere Based On Passive Microwave Remote Sensing

Frozen ground,as the main components of cryosphere,is a sensitive indicator of climate change because its intense responses to climate change.Frozen ground contains abundant information of past climate change.About 60%of near-surface soil has a phase change process between water and ice,namely the freeze/thaw cycle process.In extreme years,the extent of near-surface soil freeze can even account for more than 80%of the land surface area in Northern Hemisphere(NH).The near-surface soil freeze/thaw cycle(NSFTC)is a"switch"of land surface processes and has important influence on surface energy processes,hydrological processes,vegetation dynamics,carbon emissions and ecosystem function.Therefore,the onset and offset date of near-surface soil freeze,the number of freeze day in a year,the extent and times of near-surface soil freeze are critical indicators for research of NSFTC,which is important for understanding the interrelationship between frozen ground and climate change.There are many methods for monitoring seasonally frozen ground and permafrost.These methods can be divided into(1)traditional methods,(2)geophysical methods,(3)numerical simulation methods and(4)remote sensing methods.Passive microwave remote sensing data have the advantages of long time continuous,global coverage,short revisit cycle and multi-polarization and multi-frequency observation,which can provide the basic data for research of high-resolution near-surface soil freeze/thaw status in global scale and is the most effective technical means.However,previous research on verification of passive microwave remote sensing algorithm was limited by in-situ data,and lacked comprehensive verification of different ecosystems.At the same time,the original passive microwave satellite remote sensing data is at a resolution of25 km,far from satisfying the research of NSFTC in complex terrain and ecosystems.The objective of this study is to analyse the spatio-temperal variation of near-surface soil freeze/thaw status under climate change by using the validated near-soil soil freeze/thaw detection algorithm and improved high-resolution(3.125 km)passive microwave remote sensing data.Finally,we can establish a high-resolution long-time series near-surface soil freeze/thaw data set in NH,and to provide reliable scientific data support for the study of global change,ecosystem,carbon cycle,and hydrological processes.Based on the 25 km Calibrated Passive Microwave Daily EASE-Grid 2.0Brightness Temperature ESDR(CETB)developed by National Snow and Ice Data Center(NSIDC),combined with the data of surface temperature of 0 cm in China,we evaluate and inter-compare the classification results of four most widely used freeze/thaw detection algorithms across China.The results shows that the discriminant accuracy is:Discriminant function algorithm(DFA,86.2%)>Modified seasonal threshold algorithm(MSTA,84.1%)?Single index algorithm(SIA,84.1%)>Decision tree algorithm(DTA,73.8%).DFA and DTA is based on specific training sample data to establish statistical algorithms or to calibrate the threshold of key indicators,so it is limited by study area.We finally choose SIA as the main algorithm,combined with3.125 km CETB during 1979 to 2015 in NH to identify near-surface soil freeze/thaw status and establish a dataset of near-surface soil freeze/thaw state with a resolution of3.125 km in HN from 1979 to 2015.From 1981 to 2010,the extent of near-surface soil freeze is about 62.6×10~6±2.4×10~6 km~2(occupying 64.23%±2.46%of the land area in NH).The average onset and offset date of near-surface soil freeze in NH was September 22(±40 days)and May 8(±45 days),respectively.The average duration of freeze/thaw cycle was 229±79 days.However,due to the repeated freeze/thaw phenomenon caused by the temperature fluctuation in freeze point,the average actual number of freeze days was187±84 days,42 days less than the duration.The results showed obvious latitude zonality and vertical zonality.With the increase of latitude and altitude,near-surface soil freeze started earlier and ended later,and the duration and the number of days of near-surface soil freeze were larger.Especially in Qinghai-Tibet Plateau and Siberia,the near-surface soil freeze started the earliest and ends the latest.However,in the low latitudes of NH,the average annual temperature in January is generally around 0?,indicating that near-surface soil may not be completely frozen even in the coldest month,or even if the soil temperature is temporarily below 0?,it cannot be maintained for a long time.From 1979 to 2015,the annual average temperature in NH increased at a rate of0.04?/year.In the circumstances,the onset date of near-surface soil freeze in NH was delayed at an average rate of about 1.22±0.64 day/year.The offset date of near-surface soil freeze advanced with an average rate of-0.72±0.73 day/year.The duration and actual number of freeze days were shortened at an average rate of-1.77±1.34 and-0.92±1.25 day/year,respectively.The times of near-surface freeze decreased at an average rate of 3±2 times/decade,while the changing trend of freeze days during each freeze/thaw cycle in the freezing period was not obvious.All these data indicate that global warming has a significant impact on NSFC in NH,which is mainly reflected in the reduction of the number of freeze day,delay of near-surface soil freeze and advance of near-surface soil thaw,especially at high latitude regions.The main reason may be that temperature increasing in Arctic is larger,which has a significant impact on near surface soil freeze/thaw cycle.When classifying near-surface soil freeze/thaw status by using passive microwave remote sensing brightness temperature products,the factors that affect the classification accuracy mainly include:(i)the inconsistency between brightness temperature caused by orbit deviation for different platforms or the replacement of microwave radiometer;(ii)Error introduced by high resolution image reconstruction algorithm;(iii)interpolation process for filling up the missing data because of stripe scanning of satellites;(iv)soil moisture content;(v)snow cover(especially wet snow)and(vi)fuzziness of freeze/thaw boundary during transition period.SMOS and SMAP can provide global L-band brightness temperature.Along with synchronous orbiting SSM/I and SSMIS,it forms a set of multi-source,multi-frequency,multi-angle comprehensive observation,which can provide several times measurements a day and will be the development and innovation of detection algorithms based on passive microwave remote sensing for near-surface soil freeze and thaw cycle.