Response of Surface and Atmospheric Parameters Associated Response of Surface and Atmospheric Parameters Associated With the Iran M 7.3 Earthquake With the Iran M 7.3 Earthquake

—Multiparameter observed from satellite, including microwave brightness temperature, skin temperature, air temperature, and carbon monoxide, have been analyzed to identify the anomalous signals associated with the M 7.3 Iran earthquake of November 12, 2017. Besides removing the multiyear variability of parameters as background, the effect of surface and atmosphere of a dust storm event in Middle East region during October 29– November 1 is considered to distinguish the possible anomalies associated with the earthquake. The characteristic behaviors of surface and atmospheric parameters clearly show the signals associated with the M 7.3 earthquake and the dust storm event. The multiple parameters at different pressure levels provide clear evidence to identify the anomalous signals associated with an earth-quake,whichcouldhelpustominimizethefalsealarms.Ourresults showtheatmosphericdisturbancescausedbyothernaturalhazardeventscouldmaskthethermalanomaliesinducedbytectonicactiv-ities,whichcannotbeignoredwhendetectingtheabnormalsurfaceandatmosphericsignalsassociatedwithearthquakeactivities.


Response of Surface and Atmospheric Parameters
Associated With the Iran M 7.3 Earthquake Feng Jing , Member, IEEE, and Ramesh P. Singh , Senior Member, IEEE Abstract-Multiparameter observed from satellite, including microwave brightness temperature, skin temperature, air temperature, and carbon monoxide, have been analyzed to identify the anomalous signals associated with the M 7.3 Iran earthquake of November 12, 2017.Besides removing the multiyear variability of parameters as background, the effect of surface and atmosphere of a dust storm event in Middle East region during October 29-November 1 is considered to distinguish the possible anomalies associated with the earthquake.The characteristic behaviors of surface and atmospheric parameters clearly show the signals associated with the M 7.3 earthquake and the dust storm event.
The multiple parameters at different pressure levels provide clear evidence to identify the anomalous signals associated with an earthquake, which could help us to minimize the false alarms.Our results show the atmospheric disturbances caused by other natural hazard events could mask the thermal anomalies induced by tectonic activities, which cannot be ignored when detecting the abnormal surface and atmospheric signals associated with earthquake activities.
Index Terms-Atmospheric variation, earthquake, microwave brightness temperature, remote sensing, satellite observation.

I. INTRODUCTION
E ARTHQUAKES are caused by movement of plates along the tectonic faults and/or stress changes due to fluid injection and water withdrawal.The identification of anomalous signals related to earthquakes is a real challenge.The surface thermal anomalies prior to earthquakes in central Asia were reported for the first time from satellite data about three decades earlier [2].Following this significant discovery, different kinds of thermal-related parameters observed by satellite, such as infrared and microwave brightness temperature [3]- [6], outgoing longwave radiation [7], [8], surface latent heat flux [9], surface temperature, and air temperature (AT) [8], [10], were used to detect thermal anomalies associated with earthquake activities around the world.Besides these thermal-related parameters, changes in atmospheric parameters such as gas emissions [11], relative humidity, and water vapor [12], [13], have also been observed prior to earthquakes using satellite data.The changes in various parameters were observed few days to few months prior to the occurrence of earthquake within the epicentral region, which also depend on other parameters such as geological, hydrological environment [14], [15].The size of epicentral region corresponding to the stress build up region depends on the magnitude of earthquake [1].The changes in the surface, atmosphere, meteorological, and ionospheric parameters are found to be associated with earthquakes in different parts of the globe and show a strong coupling [10], [14], [16]- [18].The models of Lithosphere-Atmosphere-Ionosphere coupling (LAIC) [19] and lithosphere-coversphere-atmosphere coupling [20] have been proposed to explain the coupling mechanism associated with earthquakes.Usually, the removals of long-term (annual) and short-term (seasonal) background changes have been considered to extract the abnormal signals caused by earthquakes.However, many results have revealed similar responses on surface, atmosphere and even ionosphere associated with different natural disasters (e.g., earthquake, dust storm, and volcano) [4], [21]- [30].For example, the anomalous signals in the thermal-related parameters associated with earthquake activity could be misjudged due to the interference from other natural hazards (dust storm, volcano) and human activities (crop burning) once those events occur in the same period and region.That makes it important to minimize the false seismic alerts through discriminating the characteristic behaviors related to earthquakes from nonseismic anomalous behaviors.
On November 12, 2017, a strong earthquake with magnitude 7.3 and focal depth 19 km occurred on the Iran-Iraq border near the Kermanshah province, Iran (hereafter referred to as the Iran M 7.3 earthquake).The epicenter of this earthquake is located between the boundary of Arabian and Eurasian plates (see Fig. 1), which is the largest recorded earthquake in this region since 1900 [31].The focal mechanism solution (see Fig. 1) indicates that a slightly oblique thrust fault triggered this event.The radius of the earthquake preparation region (orange circle in Fig. 1) is 1377.2km using the empirical formula proposed by Dobrovolsky et al. [1].Over one thousand aftershocks have been recorded within one month after the main earthquake event [32].According to USGS, the 2017 Iran M 7.3 earthquake caused more than 600 fatalities and 6000 people injured.The coand postseismic surface deformations related to this earthquake have been studied widely using InSAR data [33]- [37].This earthquake induced triggering of wide spread landslides [38], but no coseismic surface ruptures have been observed, that could be associated with the seismogenic fault, a blind oblique-thrust fault [32].Ding et al. [39] analyzed AMSR-2 microwave brightness temperature data and detected the earliest anomalies located in the lake appeared 51 days prior to the main earthquake, while the anomalies on the land appeared 18 days prior to the main event due to the different mechanism.Akhoondzadeh et al. [40] analyzed TEC and climatological data related to this earthquake and observed unusual ionospheric signals in 8-11 days prior to the earthquake event and the increased skin temperature and aerosol optical thickness 2-week prior to the earthquake.
Just a few days prior to the event, a massive dust storm hits the Middle East region at the end of October 2017, the epicenter and surrounding region were affected by the dust loading, which provides the possibility to study surface and atmospheric characteristics associated with the earthquake and non-seismic events like dust storm.Detailed analysis of multiparameter over the epicentral region of M 7.3 earthquake from satellites have been carried out to study the characteristic changes associated with the earthquake and dust strom event, since earthquake and dust strom event occurred at the same time.Although such cases are rare, but strong winds that generate dust storms prior to the earthquake and during and after the cyclone, earthquake events were observed in the past.The impact of a dust storm event occurred in the epicentral region prior to the earthquake has been analyzed to identify the characteristic behaviors on surface and atmospheric parameters related to the earthquake event.Our detailed analysis shows the distinct changes of surface and atmospheric parameters associated with the Iran M 7.3 earthquake, which is different with the dust event driven by the meteorological sources.

A. Satellite Data
Satellite derived microwave brightness temperature (MWBT), skin temperature (SKT), surface air temperature (SAT), and carbon monoxide (CO) data have been analyzed in detail to obtain the possible variations associated with the earthquake event.
MWBT data from the Defense Meteorological Space Program (DMSP) special sensor microwave imager/sounder (SSMIS) data for the periods 2008-2018 with a 25 km spatial resolution, and SKT, SAT, and CO data with a spatial resolution of 1.0°from atmospheric infrared sounder (AIRS) onboard the Earth Observing System data for the periods 2003-2020 have been used.The DMSP SSMIS dataset provides MWBT data at frequency 19.35, 37.0, 91.655 GHz in both vertical (V) and horizontal (H) polarizations and 22.235 GHz in vertical polarization.Only 19.35 GHz frequency with horizontal polarization has been considered based on our earlier findings related to earthquake cases in different soil moisture areas [6], [41].
We have also considered other satellite data as auxiliary data to understand the variations in multiparameter.National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) reanalysis product-surface latent heat flux (SLHF) dataset, a joint product from the NCEP and the NCAR, with spatial resolution 1.875°from NOAA has been used to obtain the heat exchange between the Earth's surface and the atmosphere.

B. Method
The detection of anomalous signal is based on the background variation as suggested by many [42]- [45].The background field and the detection of anomalous signal are obtained according to the absolutely local index of change of the environment approach proposed by Tramutoli [46].
The temporal means μ i (x, y) and the standard deviation σ i (x, y) for a certain day i were computed as background data.μ i (x, y) and σ i (x, y) are defined by the following: where V i (x, y) is the parameter value observed using satellite at the certain day i and location with latitude x and longitude y.N is the number of the years with the background data.The anomalous variation S i (x, y) is computed from following:

A. Microwave Brightness Temperature
The 5-day averaged MWBT data over the Middle East region around the time of Iran M 7.3 earthquake have been analyzed similar to our earlier studies [6], [41] to avoid the missing values due to satellite coverage.The 11-year data from 2008 to 2018 have been used to calculate the background values.Every 5-day residual values by removing the 11-year averaged values have been computed (see Fig. 2).From the spatial distribution of residual values in the Middle East, a pronounced MWBT anomaly along the Arabia-Eurasia plate boundary was observed around the epicentral region (see Fig. 2).An enhanced MWBT appears from late October and continued until one day prior to the main earthquake event.After five days later, the enhanced MWBT appeared again on the same region that could be caused by a series of moderate aftershocks during 17-20 November (M 4.5 on 17, M4.7 on 18, M 4.5, and M 4.9 on 20), afterwards frequency and magnitude of the aftershocks decline until December 6 (see Fig. 3).A small enhancement in MWBT during November 27 to December 6 is associated with two earthquakes of M 4.8 on December 6 and a M 5.4 earthquake on December 11 in this region (see Fig. 3).We further analyzed daily data to find out the starting day of the enhanced MWBT although there are gaps in data due to satellite coverage (see Fig. 4).A pronounced increase in MWBT within the epicentral region was observed on October 26, 2017 that disappeared 5 days later, which is consistent with the observation using AMSR-2 microwave brightness temperature data [39].Again, on November 6, 2017, an enhancement in MWBT was observed until one day prior to the main earthquake (no data was available over the epicentral region during November 9/10, 2017 due to gap in satellite coverage).Afterwards MWBT enhanced during November 19-21, 2017, and two aftershocks (M 4.5 and M 4.9) occurred November 20, 2017.Furthermore, MWBT was found to enhance during November 29/30-December 6/7, 2017 that could be associated with the two M 4.8 earthquakes on December 6 and a M 5.4 earthquake  on December 11 (see Fig. 3).The distribution of enhanced MWBT was observed along the boundary of the Arabian and Eurasian plates that could be associated with tectonic activities, as suggested by other strong earthquakes around the world [5], [6], [10], [41], [47].

B. Skin Temperature
The anomalous skin temperature (SKT) has been obtained based on 18-year (2003-2020) background data using the method discussed earlier (see Section II-B).The SKT variations in the epicentral region (34°-35°N, 44°-46°E) during October/November 2017 show two peaks within 2-week prior to the main event on November 12, 2017 [see Fig. 5(a)].The first peak was observed in late October and the second peak was observed in early November.The SKT data of October 28 and November 4 in the epicentral region are missing due to gap in satellite coverage.The SKT enhanced on October 29 and November 7, which is more than 2 times standard deviation compare to the background value as defined by (3).The SKT values on October 27 and November 3, 9 exceeded the line showing 1.5 times of standard deviation.From the spatial distributions of the distinct increase in SKT, we observed the high values of SKT [see Fig.

C. Surface Air Temperature
The AIRS SAT data over the epicentral region (32°-34°N, 45°-46°E) during the period of October/November 2017 show more than 1.5 times of the standard deviation in two stages showing two prominent peaks [see Fig. 6(a)].The first peak was observed during October 25-30 and the second peak during November 3-7, 2017, which is consistent with the change in SKT [see (Fig. 5(a)].The spatial distributions of SAT on October 27 and 29 clearly show the enhanced values over the most parts of the Middle East region, the values were observed to be much higher compared to SKT values during the same period [see Fig. 6(b)  and (c)].The areal distribution was also found to be higher.On October 31, the enhanced SAT values were low, and the coverage showed northward [see Fig. 6(d

D. Carbon Monoxide
During a number of earthquakes, enhancement in CO were observed over the epicentral region prior, during and after the earthquake event [10], [11], [41], [48].We have computed variations in CO Volume Mixing Ratio (COVMR) at the pressure level 925 hPa over the epicentral region (32°-34°N, 44°-46°E) during 2017 October/November.Considering higher topography of the epicentral region, CO at the pressure level of 925 hPa have been analyzed.An abrupt increase in CO after the occurrence of M 7.3 earthquake was observed [see Fig. 7(a)].The increased CO value on November 14, 2017 (two days after the main event) exceeds the 2 times of standard deviation.The data on November 13 are not available due to the orbital gap in satellite coverage.Fig. 7(b)-(d) shows the pronounced increase in CO at the lower troposphere around the epicentral region within one week after the Iran M 7.3 earthquake, that could be related to the high-frequency and high-magnitude aftershock activities during this period (see Fig. 3).We did not find an enhancements in CO prior to the main event, which could be attributed to the presence of blind seismogenic fault.

A. Dust Storm Event Prior to the M 7.3 Iran Earthquake
We observed the two abnormal peaks in SKT and SAT, one peak prior to the Iran earthquake, which occurred in late October and the second one appeared within one week prior to the main earthquake event, showing different behaviors in magnitude and coverage.By checking the Suomi NPP VIIRS image from NASA Worldview, 1 we observed the presence of a massive dust storm over the Middle East region at the end of October in 2017 (see Fig. 8).The dust storm affected the northern Saudi Arabia, Iraq, western Iran, and Kuwait due to strong winds.The low visibility and poor air quality were reported. 2he 3-day averaged (from October 30-November 1, 2017) MODIS AOD shows high values over these regions [see Fig. 9(a)].The AOD and AE data during the months 2017 October/November from AErosol RObotic NETwork (AERONET) IASBS station in Iran [located 300 km northeast of the epicenter, red triangle in Fig. 9(a)] have been analyzed.The highest AOD and corresponding low AE were observed during October 31-November 1 [see Fig. 9(b)], which can reflect the dominance of coarse particles during dust loading due to the difference in spectral dependence of AOD [49], [50].

B. Variations of SKT and SAT
The first increased SKT and SAT occurred prior to the dust loading (October 27 and 29), which were observed mainly covering the northern regions of Saudi Arabia, Iraq and Iran and distributed along the north-east direction [see Figs.AOD region observed in Fig. 9(a) as the source (the geolocation is 26.7°N, 38.9°E, which is located on the west boundary of An Nafud desert), and computed the 36-h forward trajectories of air masses at 1200 UTC, October 25 and 27, 2017 using NOAA HYSPLIT model [51].The forward trajectories clearly found to be consistent with the distribution of enhanced SKT and SAT on October 27 and 29, 2017 due to transport of air mass (see Fig. 10).The increase in SKT and SAT were observed prior to the onset of dust by others [52].We also observed an enhancement in SAT with large values during this period compared with SKT on the same day.The high spatial distribution of SAT values indicates the source of enhanced temperature could be associated with the atmosphere not any change in surface or subsurface in the lithosphere.The temporal distribution of SKT and SAT in the epicentral region during the period October 30-November 2, 2017 shows decreasing values [see Figs.5(a) and 6(a)], which can be attributed to the loading of dust particles in the atmosphere that reflect the solar radiation outward that reduce the surface temperature.
The second peak of SKT and SAT occurred within one week prior to the main earthquake event.The spatial distribution of SKT and SAT on November 3, 5, and 7, 2017 is within the The SKT variations within the epicentral region was found to be higher compared to SAT on the same day, showing observed changes could be associated with tectonic activities and surface/subsurface perturbations.In the absence of water well data, it is difficult to relate with the deeper source of the observed changes.

C. Variations of AT and CO at Different Altitudes
The AT and CO over the epicentral region at different pressure levels derived from AIRS during the time of dust storm event in October 2017 and the Iran M 7.3 earthquake in November are shown in Fig. 11.We observed the lowest value in AT near the surface at the pressure level 925 hPa and the highest at the pressure levels 500-700 hPa during the dusty days (October 31-November 1, 2017) [see Fig. 11(a)], that associated with the strong vertical motion and upward convective activities caused by strong winds during dust storm event.While the distinct enhance in AT on November 7, 2017 [see Fig. 11(b)], which is consistent with the day of enhanced SKT and SAT around the epicenter [see Figs.5(g) and 6(g)].The increase in AT only occurred at the near surface (850-925 hPa), that could be likely due to stress buildup in the epicentral region prior to the earthquake event [10].
Dust storm and mixing with local anthropogenic emissions could cause changes in CO as observed by many [11], [48], [53].The COVMR variations at the pressure levels 500-925 hPa, correspond to the low and middle troposphere, were observed on dusty October 30, 2017 [see Fig. 11(c)], that could be attributed to the convective upward movements under the influence of strong wind as reported in other dust storm events [48], [52].Fig. 8 shows the movement of dust plumes over the epicentral region on October 30, 2017 compared with two earlier days.On the contrary, the high COVMR values in the lower troposphere have been observed after the occurrence of Iran M 7.3 earthquake [see Fig. 11(d)].The maximum COVMR value of 144.5 ppbv appeared at pressure level 925 hPa that close to the surface two days after the main earthquake event (the data on November 13 are unavailable due to the orbital gap in satellite coverage), which could be attributed to the degassing from deep crust through the fault and fracture zones [54], [55].The vertical profile of CO clearly shows the major contribution of the increased CO on November 14, 2017 [see Fig. 7(b)] that could be related to the release of CO along the plate boundary.

D. Evidence From SLHF
The SLHF reflects the heat emits from the earth's surface (both land and ocean) to the atmosphere, that is associated with evaporation of water at the surface.In this process, water vapor condenses on the atmospheric ions and hydrated ions move upward.We have analyzed SLHF data from the NCEP/NCAR reanalysis products.SMAP soil moisture and TRMM near real-time precipitation rate data have also been considered to understand the SLHF variations.SLHF variations over the epicentral region were computed by removing the 18-year (2003 to 2020) background averaged value.We observed that the SLHF variation is closely related to the precipitation rate (see Fig. 12).The low SLHF values during the period of dust loading, could be attributed to the absorption of water vapor by dust particles.The changes in SLHF provide evidence for the existence of disturbance between the surface and the atmosphere during the dust storm loading.The decrease in SLHF during the dust storm has been observed by others [52].We also observed enhancement in both SLHF and soil moisture on November 5, 2017, but it was difficult to relate the changes to the earthquake considering the higher precipitation rate 1-2 days ago, although the enhancement in SLHF has been observed prior to a number of earthquakes [9], [10], [56], [57], and increased soil moisture observed prior to the Nepal M 7.8 earthquake [10], which could be attributed to the fluctuation of water level in the epicentral region associated with the strong earthquake events.

E. Confutation Analysis
To check whether the similar variations exist during the same period without earthquake-affected, we have considered MWBT, SKT, and SAT data in 2015 for the detailed analysis.The selection of 2015 is considering no earthquake with magnitude greater than 5.5 within a radius of 1000 km from the epicenter of 2017 M 7.3 Iran earthquake.We did not observe MWBT anomalies (supplementary Figure S1).Two peaks (on October 1 and 27, 2015) in SKT with more than 2 times of standard deviation in the same region with the Iran M 7.3 earthquake have been observed (supplementary Figure S2a).However, the spatial distributions of SKT and SAT show the different pattern (with larger spatial scale and only last for one day.See supplementary Figure S3), compared with the Iran earthquake (showing local variations and time continuity) [see Figs.An increase in CO was observed on November 25, 2015 (supplementary Figure S4), that disappeared next day although it was  local distribution (supplementary Figure S5).More importantly, the variations in these parameters do not show the characteristics of quasi synchronization proposed by the deviation-time-space criterions for earthquake anomaly recognition using multiparameter [58].

V. DISCUSSION
In this article, we observed the anomalous variations in multiparameter from satellite data, including MWBT, SKT, AT, CO associated with the 2017 M 7.3 Iran earthquake by considering not only removing the multiyear background, but also the impact of dust storm event in Middle East region during October 29-November 1, 2017.
The cause of the earthquake could be tectonic movement that causes change in stress within the epicentral region prior to the earthquake event.Our earlier studies show the bottom-up pattern for anomalous multiparameter at the different altitudes prior to strong earthquakes [10], [59].In this article, MWBT shows anomalous signal prior to the occurrence of earthquake (about 2 weeks in advance) although MWBT was weaken by the increased soil moisture during the same period.Our results from SSMIS MWBT are found to be consistent with the result using the AMSR-2 MWBT data by Ding et al. [39].An increase in MWBT around the epicenter is a response to the thermal variations on the subsurface related to the tectonic activities [6], [41].The MWBT variations are not easily affected by the events driven by the meteorological sources.Akhoondzadeh et al. [40] observed an increase in SKT 15-day prior to this earthquake, but the influence of dust storm event during this period in this region was ignored.Here, we detected increase in SKT and SAT within one week prior to the main earthquake by eliminating the impact of dust storms.During this period, the SKT was observed to be higher than SAT, and the spatial distributions were around the epicentral region.The vertical profile of AT associated with earthquake activity shows the high value at lower troposphere (850-925 hPa), that could be due to the stress buildup process within the epicentral region.The surface thermal signals are difficult to transmit to the higher altitude (e.g., middle to high troposphere) as the result of atmospheric diffusion effect, small changes in SAT are found compared to SKT.The similar AT behavior prior to the earthquake has been reported by Ma et al. [60].The abrupt increase in CO distributed around the epicentral region at the lower troposphere after the earthquake could be related to the degassing from deep crust along the fault cracks or the fractured rocks as we observed in the 2001 Kokoxili M 7.8 earthquake [41].An enhancement in SLHF one week prior to the main earthquake event has also been observed, but it is hard to comment its relationship with the impending earthquake considering the influence of precipitation, although it is very much associated with the geological and hydrological environment.
All the multiparameter considered show anomalous variations in late October 2017, which may not be related to seismic event that could be related to the dust storm observed during the same period.The dust storm caused by strong winds lifting dust particles into the atmosphere.The strong upward convection exists during this period.An enhancement in SAT prior and during the onset of dust particles could be associated with the movement of the air mass from desert under the effect of horizontal movement as observed from the 36-h forward trajectories.The decrease in SKT during the dusty days can be attributed to the reflection of the solar radiation by the dust particles that provides cooling effect on the surface during the dusty days.The decline of AT during the dusty days only occurred on the surface and lower atmosphere compared with the values in the earlier days reflected in the vertical profile of AT, that could be related to the strong vertical motion and upward convective activities.The increase in SAT is found to be greater than SKT due to the convection of dust storm from lower atmosphere is another important characteristic to discriminate from seismic anomalies.In addition, CO in the lower atmosphere decrease under the strong vertical advection caused by winds and the decease SLHF due to the absorption of water vapor by dust particles in late October 2017 also suggest that the surface and the atmosphere are affected by dust storm event during this period.

VI. CONCLUSION
In this article, we provide the valuable evidence to identify the earthquake-induced unusual variations through the spatial distribution of surface parameters and vertical profile of atmospheric parameters considering the different driven sources (tectonic-driven during the impending earthquake stage and meteorological-driven during the dusty-days), which will help us to identify the anomalous signals associated with strong earthquake activities.
During the final stage of strong earthquake preparation, multiple parameters at different altitudes could show nearsynchronous changes.With the build-up of tectonic stress, MWBT enhancement occurred at the earliest due to the response on the subsurface.Afterwards SKT and AT within the earthquake preparation region will increase.During this period, other parameters like latent heat flux and relative humidity may also change, but that depends on the hydrological and atmospheric environment (e.g., soil moisture and water vapor).That could be the reason that SLHF anomalies are more likely to be observed prior to the coastal earthquakes [9], [56], [61].Due to the release of latent flux, the water vapor condense on the atmospheric ions and move up with more water molecules that could be observed due to the enhanced AOD [19].But in this article, we did not see any obvious changes in SLHF and AOD associated with the Iran M 7.3 earthquake.The emission of gases from the active fault zones prior and after the occurrence of earthquake has also been observed from satellite [11], [54], [59].The near-synchronous variations on the multiple parameters in surface/subsurface and atmosphere show strong coupling between lithosphere and atmosphere associated with the impending earthquake as suggested by LAIC model [19].
In this case, the increased MWBT during the dusty days should be independent of dust storm event in view of a good spatial consistency with the boundary of tectonic plates and epicentral region.Comparatively, the variations in SKT and SAT only show a clear relationship with dust storm instead of earthquake during the same period.The possible reason could be associated with the strong atmospheric disturbances caused by dust storm masks the thermal anomalies reflected on SKT and SAT induced by tectonic activities.Therefore, the atmospheric disturbances cannot be ignored when detecting the abnormal atmospheric signals associated with earthquake.

Fig. 1 .
Fig. 1.Epicenter (red star) location and focal mechanism solution (source: GCMT) of earthquake M=7.3 of November 12, 2017.Base map source is ETOPO5 5-min gridded elevation data.The earthquake preparation region were computed using the formula from Dobrovolsky et al. [1].
The 18-year (2003-2020) SLHF data have been considered in the present analysis.NASA Soil Moisture Active Passive (SMAP) 36 km×36 km soil moisture and Tropical Rainfall Measuring Mission (TRMM) 0.25°× 0.25°s patial resolution near real-time precipitation rate data have been used in the present study to analyze the SLHF variations.In addition, the 1.0-degree aerosol optical depth (AOD) product from the Moderate Resolution Imaging Spectroradiometer (MODIS) is used to study the aerosol parameters (AOD and Ångström Exponent -AE) during the dust storm event.

Fig. 2 .
Fig. 2. Spatial distribution of five-day averaged land MWBT variations around the time of Iran M 7.3 earthquake.Red star shows the location of epicenter and red line shows the plate boundary.

Fig. 3 .
Fig. 3. Temporal distribution of magnitude and frequency for the aftershocks (M > 4) within one month of the Iran M 7.3 earthquake.Only the maximum magnitude is shown in every single day.

Fig. 4 .
Fig. 4. Spatial distribution of daily land MWBT variations around the time of Iran M 7.3 earthquake.Red star shows the location of epicenter and red line shows the plate boundary.

Fig. 5 .
Fig. 5. Spatial-temporal variations of skin temperature within the epicentral region of M7.3 earthquake.(a) Temporal variations during the months October/November 2017.(b)-(g) Spatial variations on October 27, 29, and 31, November 3, 5, and 7, 2017.Black arrow and red star show the earthquake date and epicenter of the Iran M 7.3 earthquake, respectively.Red line shows the plate boundary.
5(b) and (c)] mainly covered the northern regions of Saudi Arabia on October 27 and 29, and afterwards moved over the northern parts of Iran on October 31 [see Fig. 5(d)].The increased SKT distributed along the north-east direction during
)].The second SAT peak value was distributed within the epicentral region on November 3, 5, and 7, 2017 [see Fig. 6(e)-(g)].The variations in SAT during this stage show lower values compared to SKT during the same period [see Fig. 5(e)-(g)].The SAT data of October 28 and November 4 and 6 are not shown due to the gap in satellite coverage over the epicentral region.

Fig. 7 .
Fig. 7. Spatial-temporal variation of COVMR at 925 hPa associated with the Iran M 7.3 earthquake.(a) Temporal variations in COVMR during the October/November 2017 over the epicentral region.(b)-(d) COVMR variations on November 14, 17, and 18, 2017.Black arrow shows the day of earthquake.Red star indicates the epicenter of Iran M 7.3 earthquake.Red line shows the plate boundary.
5(b), (c) and 6(b), (c)].We took the point at the western part of the high

Fig. 8 .
Fig. 8. Dust plume in the Middle East region from October 28-November 2, 2017.Source: NASA Worldview, Suomi NPP VIIRS image.Red star shows the epicenter of Iran M 7.3 earthquake.

Fig. 9 .
Fig. 9. Temporal-spatial distribution of AOD observed by satellite and ground station.(a) Three-day averaged MODIS AOD for the periods October 30-November 1, and (b) AOD and AE from AERONET IASBS station during October/November 2017.Higher AOD and low AE values show dust strom event.Red triangle shows the location of IASBS station.

Fig. 11 .
Fig. 11.Vertical variations of AT and CO over the epicentral region around the dust storm in October (a) and (c) and the Iran M 7.3 earthquake in the month of November 2017 (b) and (d).

Fig. 12 .
Fig. 12. Temporal variations in surface latent heat flux, precipitation rate and soil moisture from October/November 2017 over the epicentral region of Iran M 7.3 earthquake.